CN112286184B - Outdoor surveying robot control method based on 5G network - Google Patents
Outdoor surveying robot control method based on 5G network Download PDFInfo
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Abstract
The invention relates to the technical field of outdoor survey, in particular to a control method and a control system of an outdoor survey robot based on a 5G network, wherein the robot control system is in communication connection with an intelligent terminal through the 5G wireless network, and comprises the following components: the system comprises a main control module, a navigation positioning module, an image recognition module, a sensor module, a motor driving module and a storage module, wherein the navigation positioning module, the image recognition module, the sensor module, the motor driving module and the storage module are respectively connected with the main control module; the driving path of the robot is mastered in real time through a navigation positioning module; identifying a target object through an image identification module; the method comprises the following steps of detecting obstacles around the robot through a sensor module, and driving the robot to run through a motor driving module; recording the position information and the image information through a storage module; the robot is controlled by the main control module in response to the control instruction issued by the intelligent terminal, and the success rate of the outdoor operation of the robot and the flexibility of coping with outdoor complex environments are greatly improved.
Description
Technical Field
The invention relates to the technical field of outdoor surveying, in particular to a control method and a control system of an outdoor surveying robot based on a 5G network.
Background
Outdoor work refers to work outside a residence at a work site. Such as field survey, sanitation cleaning, mountain picking, etc. The area of mountainous regions in China accounts for 70% of the total area, and the mountainous regions have abundant natural resources, but are influenced by the terrain and climate environment, so that mountain operation has certain risk. Outdoor operations are easily affected by the environment, and if the work place can be known in advance, the influence of the environment on the outdoor operations can be greatly reduced. The remote control robot is one of the solving strategies, and the remote control robot is used for remotely controlling the remote end in real time, which is an important means for liberating productivity. The key problems of the success of remote control are the master-slave system operation consistency and real-time performance of the robot, including the technical problems of signal stability, anti-interference performance, high-throughput signal transmission and the like. The development of the 5G network solves the key problem and greatly promotes the development of the intelligent industry.
In the prior art, the STM 32-based mine survey robot control system of 201911173667.0 in the patent application number improves the integration level of the mine survey robot control system by using a motor driving control chip of the STM32, and the upper computer issues an instruction to drive the motor, so that the aim of controlling the mine survey robot to survey is achieved. The patent application number is 201810851723.0's a photography robot that outdoor surveying was used utilizes multiple telescopic link and rotates the motor to come the remote control camera, realizes the diversified shooting of multi-angle of multiple outdoor environment through the remote control camera.
However, the existing robot for surveying is not popularized yet for the application of 5G network large flow, and the remote control function is single, so that the requirements of various outdoor operations cannot be met.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method and a system for controlling an outdoor surveying robot based on a 5G network, so as to solve one or more technical problems in the prior art, and provide at least one useful choice or creation condition.
In order to achieve the above object, the present invention provides the following technical solutions:
a robot control system surveys in open air based on 5G network, the robot control system passes through 5G wireless network and intelligent terminal communication connection, the robot control system includes: the system comprises a main control module, a navigation positioning module, an image recognition module, a sensor module, a motor driving module and a storage module, wherein the navigation positioning module, the image recognition module, the sensor module, the motor driving module and the storage module are respectively connected with the main control module;
the navigation positioning module is used for providing a running path of the robot for the main control module;
the image recognition module is used for shooting an image, extracting an object area image in the image, comparing the characteristics of the object area image and a target object image, and judging whether the object area image contains a target object;
the storage module is used for storing the object area image, and the object area image is used for sending the object area image to the storage module for recording when the object area image is judged to contain the target object;
the sensor module is used for detecting obstacles around the robot and reporting the relative position information of the obstacles and the robot to the main control module;
the motor driving module is used for driving the robot to operate according to the operation instruction of the main control module;
the storage module is used for recording position information and image information; the position information comprises position information of a target object, an initial position of the robot and a driving path of the robot; the image information includes an object region image of the target object;
and the main control module is also used for responding to a control instruction issued by the intelligent terminal to control the operation of the motor driving module in real time.
A control method of an outdoor surveying robot based on a 5G network is applied to a robot control system, the robot control system is in communication connection with an intelligent terminal through the 5G wireless network, and the robot control system comprises: the system comprises a main control module, a navigation positioning module, an image recognition module, a sensor module, a motor driving module and a storage module, wherein the navigation positioning module, the image recognition module, the sensor module, the motor driving module and the storage module are respectively connected with the main control module;
the method comprises the following steps:
s100, a main control module triggers a navigation positioning module to detect the initial position of the robot and transmits the initial position of the robot to an intelligent terminal in real time;
step S200, when the intelligent terminal receives the initial position of the robot, map software is started, and the initial position of the robot is displayed in the map software;
s300, the intelligent terminal carries out road planning according to the set area to be detected and the initial position of the robot so as to determine a planned path of the robot;
s400, the main control module controls a motor driving module to drive the robot to run according to the planned path, and starts an image recognition module, a sensor module and a storage module to work;
step S500, when the image recognition module recognizes a target object, triggering the main control module to send an object area image containing the target object and positioning information of the target object to a storage module for recording;
step S600, when the sensor module detects obstacles around the robot, reporting the relative position information of the obstacles and the robot to the main control module so that the main control module can adjust the running path of the robot;
step S700, the main control module reports the position information and the image information recorded by the storage module to the intelligent terminal in real time; the position information comprises positioning information of a target object, an initial position of the robot and a running path of the robot; the image information includes an object region image of the target object.
Further, the step S300 includes:
dividing a region to be detected into a plurality of grids, and determining path nodes according to the grids;
and determining the shortest path of the robot from the initial position to all the path nodes according to the path nodes, and taking the shortest path as a planning path of the robot.
Further, in the step S500, the object area image of the target object is generated by the image recognition module and reported to the main control module, and the positioning information of the target object is generated by the navigation positioning module and reported to the main control module.
Further, the step S500 includes the steps of:
the robot starts an image recognition module to shoot an image in the driving process, extracts an object area image in the image, compares the characteristics of the object area image and a target object image, and judges whether the object area image contains a target object or not;
and when the object area image is judged to contain the target object, controlling the image recognition module to stop scanning, controlling the motor driving module to stop running, sending the object area image to the storage module for recording, and then restarting the image recognition module and the motor driving module to work.
Further, before the step S100, the method further includes the following steps:
step S101, the intelligent terminal sends a connection request to the robot control system through a 5G wireless network, and after the identity authentication is passed, the intelligent terminal obtains the operation authority of the robot control system;
and S102, the intelligent terminal sends a starting instruction to the robot control system to trigger the main control module to start the navigation positioning module, the image recognition module and the sensor module.
Further, after the step S700, the method further includes: and controlling the robot to return according to the planned path.
The invention has the beneficial effects that: the invention discloses a control method and a system of an outdoor surveying robot based on a 5G network, wherein the driving path of the robot is mastered in real time through a navigation positioning module; identifying a target object through an image identification module; the method comprises the following steps of detecting obstacles around the robot through a sensor module, and driving the robot to run through a motor driving module; recording the position information and the image information through a storage module; the robot is controlled by the main control module in response to the control instruction issued by the intelligent terminal, and based on the 5G communication technology, the success rate of the outdoor operation of the robot and the flexibility of coping with outdoor complex environments are greatly improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic structural diagram of a 5G network-based outdoor survey robot control system in an embodiment of the invention;
fig. 2 is a schematic flow chart of a control method of the outdoor surveying robot based on the 5G network in the embodiment of the invention.
Detailed Description
The conception, specific structure and technical effects of the present disclosure will be described clearly and completely with reference to the accompanying drawings and embodiments, so that the purpose, scheme and effects of the present disclosure can be fully understood. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Referring to fig. 1, an embodiment of the present invention provides an outdoor surveying robot control system based on a 5G network, where the robot control system is in communication connection with an intelligent terminal through a 5G wireless network, and the robot control system includes: the system comprises a main control module, a navigation positioning module, an image recognition module, a sensor module, a motor driving module and a storage module, wherein the navigation positioning module, the image recognition module, the sensor module, the motor driving module and the storage module are respectively connected with the main control module;
the navigation positioning module is used for providing a running path of the robot for the main control module;
in one or more embodiments, the navigation and positioning module comprises at least one of a GPS positioning system and a beidou satellite navigation system, and the driving path of the robot can be displayed in real time by internally installing map software such as a Baidu map and a Gaudi map.
The image recognition module is used for shooting an image, extracting an object area image in the image, comparing the characteristics of the object area image and a target object image, and judging whether the object area image contains a target object;
and the storage module is used for sending the object area image to the storage module for recording when the object area image is judged to contain the target object.
In an embodiment, the image recognition module includes a high-definition camera, and obtains an image by controlling the high-definition camera to shoot, and performs real-time processing on the image to extract an object region image in the image, for example, an edge extraction algorithm is used to extract an image region of an object in the image to obtain the object region image, and a Can ny algorithm is used in this embodiment to perform edge extraction. Next, the object region image is compared with the target object image, and since the outdoor survey is performed to determine whether an outdoor object is a target object, the determination criterion is mainly a shape contour, and it is difficult to use the color of the object as a determination criterion, in this embodiment, SSIM (Structural SIMilarity) is used as an index for measuring the SIMilarity between the object region image and the target object image, and the value range is 0 to 1, and when two images are identical, the value of SSIM is equal to 1, in this embodiment, the threshold value of SSIM is set to 0.96, and when the value of SSIM is greater than 0.96, it is determined that the object region image includes the target object.
The sensor module is used for detecting obstacles around the robot and reporting the relative position information of the obstacles and the robot to the main control module;
in one embodiment, the sensor module comprises a vision sensor and a laser radar sensor, and the vision sensor and the laser radar sensor are arranged on the periphery of the robot so as to detect obstacles around the robot.
And the motor driving module is used for driving the robot to operate according to the operation instruction of the main control module.
In one embodiment, the motor driving module drives the robot to operate according to an operation instruction, where the operation instruction may be generated according to a pre-stored control program or may be sent by the intelligent terminal in real time.
The storage module is used for recording position information and image information;
the position information comprises position information of a target object, an initial position of the robot and a driving path of the robot; the image information includes an object region image of the target object.
When the robot is disconnected, a recording function similar to a black box can be provided, and post analysis is facilitated.
The main control module is also used for responding to a control instruction issued by the intelligent terminal to control the operation of the motor driving module in real time.
In the embodiment, the intelligent terminal can control the operation of the robot after acquiring the operation authority of the robot control system; the intelligent terminal is used for displaying the driving state of the robot motor, displaying warning if the robot fails, and displaying normal if the robot works normally; and a power reserve bar for displaying the robot.
Referring to fig. 2, an embodiment of the present invention further provides a control method for an outdoor survey robot based on a 5G network, where the method is applied to a robot control system, the robot control system is in communication connection with an intelligent terminal through a 5G wireless network, and the robot control system includes: the system comprises a main control module, a navigation positioning module, an image recognition module, a sensor module, a motor driving module and a storage module, wherein the navigation positioning module, the image recognition module, the sensor module, the motor driving module and the storage module are respectively connected with the main control module;
the method comprises the following steps:
s100, a main control module triggers a navigation positioning module to detect the initial position of the robot and transmits the initial position of the robot to an intelligent terminal in real time;
step S200, when the intelligent terminal receives the initial position of the robot, map software is started, and the initial position of the robot is displayed in the map software;
s300, the intelligent terminal carries out road planning according to the set area to be detected and the initial position of the robot so as to determine a planned path of the robot;
in one embodiment, the area to be detected may be a map area set by a user after the intelligent terminal starts map software, or a preset detection area may be loaded into the map software. And planning a road according to the set area to be detected and the initial position of the robot, so that the robot starts from the initial position and runs along the planned road, and the detection of the area to be detected can be finished.
S400, the main control module controls a motor driving module to drive the robot to run according to the planned path, and starts an image recognition module, a sensor module and a storage module to work;
step S500, when the image recognition module recognizes a target object, triggering the main control module to send an object area image containing the target object and positioning information of the target object to the storage module for recording;
the object area image of the target object is generated by the image recognition module and reported to the main control module, and the positioning information of the target object is generated by the navigation positioning module and reported to the main control module;
step S600, when the sensor module detects obstacles around the robot, reporting the relative position information of the obstacles and the robot to the main control module so that the main control module can adjust the running path of the robot;
step S700, the main control module reports the position information and the image information recorded by the storage module to the intelligent terminal in real time;
the position information comprises positioning information of a target object, an initial position of the robot and a driving path of the robot; the image information includes an object region image of the target object.
In a preferred embodiment, the step S300 includes:
dividing a region to be detected into a plurality of grids, and determining path nodes according to the grids;
and determining the shortest path of the robot from the initial position through all the path nodes according to the path nodes, and taking the shortest path as a planning path of the robot.
In a preferred embodiment, the step S300 includes the steps of:
step S310, dividing a region to be detected into a plurality of rows and a plurality of columns at the same interval to obtain M square grids with the same size, and taking the central point of each square grid as a path node of the robot to obtain M path nodes;
obviously, each row of path nodes is located at the same longitude, and each column of path nodes is located at the same latitude; in this embodiment, in order to ensure that all the target objects in the region to be detected can be detected, the side length of the grid is smaller than the identification range of the image identification module, in this embodiment, the side length of the grid is 1 meter.
Step S320, obtaining coordinates of M path nodes, taking the initial position of the robot as a starting point, and taking any path node adjacent to the starting point left and right as an end point;
in this embodiment, the initial position of the robot is a path node.
Step S330, dividing all path nodes into two parts: a path node set P with a known shortest route and a path node set Q with an unknown shortest route, a path node recorded in the set P by a P [ i ] array, and a path node recorded in the set Q by a Q [ j ] array, wherein i is more than or equal to 1 and less than or equal to M, and j is more than or equal to 1 and less than or equal to M;
obviously, after initialization, there is only one path node, i.e., the starting point, in the set P of path nodes for which the shortest path is known. For a certain path node i, if book [ i ] =1, this path node is in the set P, and if book [ i ] =0, this path node is in the set Q.
Step S340, setting the starting point as a planning point, taking the path from the planning point to the starting point as an initial path dist [ S ], if a path node i which can be directly reached by the planning point exists, updating the initial path dist [ S ] of the planning point to a shortest path dist [ S ] + e [ S ] [ i ], and setting the shortest path of a residual path node (namely, the path node which can not be directly reached by the planning point) as ∞, wherein e [ S ] [ i ] represents the path length from the planning point to the path node i;
it can be understood that when the planning point is the starting point, the initial path dist [ s ] =0; after the planning point is updated, the initial path dis t [ s ] is updated accordingly.
Step S350, selecting a path node j (namely dist [ j ] is minimum) closest to the planning point in the set Q, and adding the path node j into the set P;
when a plurality of path nodes closest to the planning point exist, the path nodes are selected in sequence from the planning point according to the sequence that the path nodes have the same latitude, larger longitude, smaller latitude, same longitude, larger latitude, same longitude and smaller latitude compared with the planning point;
and step S360, judging whether the set Q is empty, if not, setting the path node j as a planning point and executing the step S350, if so, ending, finally obtaining a group of arrays representing the path node, and connecting the group of path nodes to be used as a planning path of the robot.
In a preferred embodiment, the step S500 includes the steps of:
the robot starts an image recognition module to shoot an image in the driving process, extracts an object area image in the image, compares the characteristics of the object area image and a target object image, and judges whether the object area image contains a target object or not;
and when the object area image is judged to contain the target object, controlling the image recognition module to stop scanning, controlling the motor driving module to stop running, sending the object area image to the storage module for recording, and then restarting the image recognition module and the motor driving module to work.
In a preferred embodiment, the step S600 includes the steps of:
in the running process of the robot, detecting the relative position information of the obstacle and the robot through a sensor module; if the obstacle in the driving direction is judged to block, the main control module executes the following steps to adjust the robot:
step S610, executing an automatic mode: the main control module sends an operation instruction to the motor driving module to drive the robot to drive to travel to a path node with the same latitude and larger longitude; and if the running direction of the robot is not blocked by an obstacle, controlling the robot to run to the next path node of the current path node in the planned path.
Step S620, if the robot driving direction is still blocked by an obstacle or the robot cannot drive (for example, the robot driving direction has a hollow), executing a manual mode:
the main control module reports an error to the intelligent terminal, the intelligent terminal issues a control instruction to the main control module through remote control, the main control module responds to the control instruction issued by the intelligent terminal to control the operation of the motor driving module in real time, so that the robot is controlled to run, after the robot is controlled to run to a next path node of a path node where the robot is located currently in a planned path, the automatic mode is switched, and the step S610 is skipped.
The driving direction of the robot is distinguished by the navigation positioning module.
In a preferred embodiment, before the step S100, the method further includes the following steps:
step S101, the intelligent terminal sends a connection request to the robot control system through a 5G wireless network, and after the identity authentication is passed, the intelligent terminal obtains the operation authority of the robot control system;
and S102, the intelligent terminal sends a starting instruction to the robot control system to trigger the main control module to start the navigation positioning module, the image recognition module and the sensor module.
In a preferred embodiment, after the step S700, the method further includes: and controlling the robot to return according to the planned path.
The invention provides a control method and a system of an outdoor surveying robot based on a 5G network for solving the defects of the traditional outdoor operation. Compared with the traditional manual operation, the method firstly avoids the risk of injury to personnel; secondly, the method is based on the transmission characteristics of low time delay, high bandwidth and large connection of a 5G communication technology, can realize real-time human-computer interaction, can reduce the risk of manual operation, can master the real-time state and task completion condition of the robot at any time through an intelligent terminal, and greatly improves the flexibility of the system and the success rate of outdoor operation.
Based on the 5G communication technology, the robot control system is not limited by information transmission capacity any more, but is used as an execution terminal to be networked with the intelligent terminal in real time, and the intelligent terminal is supported to issue tasks to the robot at any time. The intelligent terminal can carry out full-range tracking on the robot through the position information and the image information, control the running path and the running state of the robot in real time, carry out operations such as interruption, recovery and adjustment on the robot, and improve the flexibility of the system for coping with outdoor complex environments.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (5)
1. The outdoor surveying robot control method based on the 5G network is characterized in that the method is applied to a robot control system, the robot control system is in communication connection with an intelligent terminal through the 5G wireless network, and the robot control system comprises: the system comprises a main control module, a navigation positioning module, an image recognition module, a sensor module, a motor driving module and a storage module, wherein the navigation positioning module, the image recognition module, the sensor module, the motor driving module and the storage module are respectively connected with the main control module;
the navigation positioning module is used for providing a running path of the robot for the main control module;
the image recognition module is used for shooting an image, extracting an object area image in the image, comparing the characteristics of the object area image with those of a target object image, and judging whether the object area image contains the target object;
the storage module is used for storing the object area image, and the object area image is used for sending the object area image to the storage module for recording when the object area image is judged to contain the target object;
the sensor module is used for detecting obstacles around the robot and reporting the relative position information of the obstacles and the robot to the main control module;
the motor driving module is used for driving the robot to operate according to the operation instruction of the main control module;
the storage module is used for recording position information and image information; the position information comprises position information of a target object, an initial position of the robot and a driving path of the robot; the image information includes an object region image of the target object;
the main control module is also used for responding to a control instruction issued by the intelligent terminal to control the operation of the motor driving module in real time;
the method comprises the following steps:
s100, a main control module triggers a navigation positioning module to detect the initial position of the robot and transmits the initial position of the robot to an intelligent terminal in real time;
step S200, when the intelligent terminal receives the initial position of the robot, map software is started, and the initial position of the robot is displayed in the map software;
s300, the intelligent terminal carries out road planning according to the set area to be detected and the initial position of the robot so as to determine a planned path of the robot;
step S400, the main control module controls a motor driving module to drive the robot to run according to the planned path, and starts an image recognition module, a sensor module and a storage module to work;
step S500, when the image recognition module recognizes a target object, triggering the main control module to send an object area image containing the target object and positioning information of the target object to a storage module for recording;
step S600, when the sensor module detects obstacles around the robot, reporting the relative position information of the obstacles and the robot to the main control module so that the main control module can adjust the running path of the robot;
step S700, the main control module reports the position information and the image information recorded by the storage module to the intelligent terminal in real time; the position information comprises positioning information of a target object, an initial position of the robot and a running path of the robot; the image information includes an object region image of the target object;
wherein the step S300 includes:
dividing a region to be detected into a plurality of grids, and determining path nodes according to the grids;
determining the shortest path of the robot from the initial position through all the path nodes according to the path nodes, and taking the shortest path as a planning path of the robot;
the dividing the area to be detected into a plurality of grids, and determining path nodes according to the grids comprises the following steps:
step S310, dividing a region to be detected into a plurality of rows and a plurality of columns at the same interval to obtain M square grids with the same size, and taking the central point of each square grid as a path node of the robot to obtain M path nodes; each row of path nodes are located at the same longitude, each column of path nodes are located at the same latitude, and the side length of the grid is 1 meter;
the determining the shortest path of the robot from the initial position through all the path nodes according to the path nodes, and using the shortest path as a planned path of the robot includes:
step S320, obtaining coordinates of M path nodes, taking the initial position of the robot as a starting point, and taking any path node adjacent to the starting point left and right as an end point;
step S330, dividing all path nodes into two parts: a path node set P with a known shortest route and a path node set Q with an unknown shortest route, a path node recorded in the set P by a P [ i ] array, and a path node recorded in the set Q by a Q [ j ] array, wherein i is more than or equal to 1 and less than or equal to M, and j is more than or equal to 1 and less than or equal to M;
step S340, setting the starting point as a planning point, taking the path from the planning point to the starting point as an initial path dist [ S ], if a path node i which can be directly reached by the planning point exists, updating the initial path dist [ S ] of the planning point to a shortest path dist [ S ] + e [ S ] [ i ], and setting the shortest path of the residual path node to [ infinity ], wherein e [ S ] [ i ] represents the path length from the planning point to the path node i; when the planning point is the starting point, the initial path dist [ s ] =0;
step S350, selecting a path node j closest to the planning point from the set Q, and adding the path node j into the set P; when a plurality of path nodes closest to the planning point exist, the path nodes are selected in sequence from the planning point according to the sequence that the path nodes have the same latitude, larger longitude, smaller latitude, same longitude, larger latitude, same longitude and smaller latitude compared with the planning point;
and step S360, judging whether the set Q is empty, if not, setting the path node j as a planning point and executing the step S350, if so, ending, finally obtaining a group of arrays representing the path node, and connecting the group of path nodes to be used as a planning path of the robot.
2. The method as claimed in claim 1, wherein in step S500, the object area image of the target object is generated by the image recognition module and reported to the main control module, and the positioning information of the target object is generated by the navigation positioning module and reported to the main control module.
3. The control method of the outdoor surveying robot based on 5G network according to claim 2, wherein the step S500 comprises the steps of:
the robot starts an image recognition module to shoot an image in the driving process, extracts an object area image in the image, compares the characteristics of the object area image and a target object image, and judges whether the object area image contains a target object or not;
and when the object area image is judged to contain the target object, controlling the image recognition module to stop scanning, controlling the motor driving module to stop running, sending the object area image to the storage module for recording, and restarting the image recognition module and the motor driving module.
4. The control method for the outdoor surveying robot based on the 5G network according to claim 1, wherein before the step S100, the method further comprises the following steps:
step S101, the intelligent terminal sends a connection request to the robot control system through a 5G wireless network, and after the identity authentication is passed, the intelligent terminal obtains the operation authority of the robot control system;
and S102, the intelligent terminal sends a starting instruction to the robot control system to trigger the main control module to start the navigation positioning module, the image recognition module and the sensor module.
5. The control method for the outdoor surveying robot based on the 5G network according to claim 1, wherein after the step S700, the method further comprises: and controlling the robot to return according to the planned path.
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