CN110586489A - Intelligent vehicle for classifying articles based on image recognition and control method thereof - Google Patents
Intelligent vehicle for classifying articles based on image recognition and control method thereof Download PDFInfo
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- CN110586489A CN110586489A CN201910721917.3A CN201910721917A CN110586489A CN 110586489 A CN110586489 A CN 110586489A CN 201910721917 A CN201910721917 A CN 201910721917A CN 110586489 A CN110586489 A CN 110586489A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J5/00—Manipulators mounted on wheels or on carriages
- B25J5/005—Manipulators mounted on wheels or on carriages mounted on endless tracks or belts
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1679—Programme controls characterised by the tasks executed
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C2501/00—Sorting according to a characteristic or feature of the articles or material to be sorted
- B07C2501/0063—Using robots
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- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
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Abstract
The invention provides an intelligent vehicle for classifying articles based on image recognition, which comprises a vehicle body, a mechanical arm and a camera module, wherein the mechanical arm and the camera module are arranged on the vehicle body; the camera module is electrically connected with the control circuit to realize information interaction; the output end of the control circuit is electrically connected with the mechanical arm and the control end of the base of the tracked vehicle. The invention also provides a control method of the intelligent vehicle, which carries out feature recognition and template matching on the object to be recognized through the camera module so as to achieve the purpose of recognizing the object; the classification of the intelligent vehicle on the articles is realized through the microprocessor and the mechanical arm; the intelligent vehicle combines the base of the crawler vehicle, the camera module, the microprocessor and the mechanical arm, achieves the purpose of flexible driving, reduces the equipment cost and realizes accurate classification of articles.
Description
Technical Field
The invention relates to the technical field of article classification, in particular to an article classification intelligent vehicle based on image recognition and a control method of the intelligent vehicle.
Background
The existing article sorting devices are divided into two types: large-scale industrial article sorting machines and medium-and small-scale article sorting robots. The large-scale industrial article sorting machine is applied to the environment of industrial production, carries out characteristic identification to the article that volume is great, weight is heavier, then reaches the purpose of letter sorting article, but this kind of device manufacturing cost is high, and the size is great, can't move at will, only is applicable to industrial production, can't satisfy people's life to the less article of volume, carry out the demand of article classification to little space range, and the structure of this kind of device is complicated moreover, and the maintenance is difficult.
The medium and small article classification robot can be applied to scenes in daily life, and articles are identified through an image identification module carried by the robot. However, the device is high in manufacturing cost, the robot occupies a large space, the carrying is inconvenient, the cost performance of the device is not high for small-size article classification and application scenes with small space, and the market promotion oriented potential is limited.
Disclosure of Invention
The invention aims to overcome the defects of high manufacturing cost and inconvenience in carrying of the existing medium-sized and small-sized article classification robot. The technical defect of low cost performance provides an article classification intelligent vehicle based on image recognition.
The invention further provides a control method of the intelligent vehicle for article classification based on image recognition.
In order to solve the technical problems, the technical scheme of the invention is as follows:
the intelligent article classification vehicle based on image recognition comprises a vehicle body, a mechanical arm and a camera module which are arranged on the vehicle body, a tracked vehicle base arranged at the bottom of the vehicle body and a control circuit arranged on the vehicle body; wherein:
the camera module is electrically connected with the control circuit to realize information interaction;
the output end of the control circuit is electrically connected with the mechanical arm and the control end of the base of the tracked vehicle.
The mechanical arm is internally provided with a mechanical arm control module and a digital steering engine; wherein:
the input end of the mechanical arm control module is electrically connected with the control circuit;
the output end of the mechanical arm control module is electrically connected with the digital steering engine;
the digital steering engine is used for driving the mechanical arm.
The crawler base comprises crawler wheels, a direct current motor and a frame; wherein:
two groups of crawler wheels and two groups of direct current motors are arranged on the frame;
the frame is fixedly connected with the vehicle body;
the input end of the direct current motor is electrically connected with the control circuit;
and the rotating shaft of the direct current motor is fixedly connected with the rotating shaft of the crawler wheel.
The control circuit comprises a microprocessor, a motor driving module and a power supply module; wherein:
the microprocessor is electrically connected with the camera module to realize information interaction;
the microprocessor is electrically connected with the mechanical arm control module and the input end of the motor driving module;
the output end of the motor driving module is electrically connected with the direct current motor;
the power module supplies power to the microprocessor and the mechanical arm.
The control method of the intelligent vehicle for article classification based on image recognition comprises the following steps:
s1: initializing the intelligent trolley to enable the mechanical arm to move to a standby state;
s2: driving a direct current motor to enable the intelligent trolley to move and carry out real-time scanning through a camera module until a parking signal is received by a microprocessor;
s3: turning off the direct current motor to stop the intelligent trolley from moving and carrying out real-time scanning by using the camera module until the mechanical arm control module receives a control signal;
s4: judging the type of the control signal, and if the type is 'pick up', executing step S5; if the "placement" is true, go to step S6;
s5: driving the mechanical arm to pick up the article, after the picking up is finished, enabling the mechanical arm to move to a standby state and sending an operation completion signal to the microprocessor, and executing the step S7;
s6: driving the mechanical arm to place articles, moving the mechanical arm to a standby state after the placement is finished, and sending an operation completion signal to the microprocessor;
s7: the microprocessor sends a next step identification instruction for the camera module according to the operation completion signal type, and executes step S2.
Wherein, in the step S2, the camera module searches for a color patch in real time, and sends a parking signal to the microprocessor when the color patch is found.
In step S3, when the robot holds an article, the camera module identifies a placing position corresponding to the object through template matching and sends a "placing" signal to the microprocessor; when the mechanical arm does not hold the article, the camera module identifies the position of the article through shape and color and sends a pick-up signal to the microprocessor; and the microprocessor transmits the received signal to the mechanical arm control module.
In step S5, the robot arm moves to a standby state after completing the picking operation, and sends a "picking completion" signal to the microprocessor; in step S6, the robot arm moves to a standby state after completing the placing operation, and sends a "placing completion" signal to the microprocessor.
In step S7, when the microprocessor receives the pickup completion signal, it sends a template matching identification instruction to the camera module to identify the placement position corresponding to the object; and when the microprocessor receives the placing completion signal, sending a shape and color identification instruction to the camera module to identify the position corresponding to the new article.
The color block identification is divided and identified according to color threshold values corresponding to respective colors; the shape recognition adopts rapid edge detection, and the canny operator is utilized to realize the rapid edge detection and realize the shape recognition; and matching the template by utilizing an NCC template algorithm according to the recognized and shot image and the template picture to realize template matching.
In the scheme, the camera module adopts an STM32H743VIT6 chip, and can realize the functions of color identification, shape identification and other feature identification, template matching, serial port communication and the like by programming and controlling through python language, and the camera module has the advantages of small volume, light weight, easy installation and low cost.
In the scheme, the mechanical arm with 6 degrees of freedom is adopted, and 6 digital steering engines drive the mechanical arm to rotate so as to complete the picking or placing action of the articles; the mechanical arm control module adopts an STM32F103C8T6 chip, has functions of 6 paths of PWM (pulse-width modulation) steering engine control signal output, serial port communication and the like, realizes direct control of the mechanical arm and serial port communication with a microprocessor, and is programmed through C language codes.
In the scheme, the microprocessor adopts an STM32F105RBT6 chip, has the functions of motor driving module and serial port communication and the like, and is programmed by using C language codes.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention provides an intelligent vehicle for classifying articles based on image recognition and a control method of the intelligent vehicle, wherein the purpose of recognizing the articles is achieved by carrying out feature recognition and template matching on the articles to be recognized through a camera module; the classification of the intelligent vehicle on the articles is realized through the microprocessor and the mechanical arm; the intelligent vehicle combines the base of the crawler vehicle, the camera module, the microprocessor and the mechanical arm, achieves the purpose of flexible driving, reduces the equipment cost and realizes accurate classification of articles.
Drawings
FIG. 1 is a schematic diagram of a circuit module connection of an intelligent vehicle;
FIG. 2 is a schematic flow chart of a control method;
wherein: 1. a mechanical arm; 11. a mechanical arm control module; 12. a digital steering engine; 2. a camera module; 3. a control circuit; 31. a microprocessor; 32. a motor drive module; 33. a power supply module; 4. a direct current motor.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Example 1
As shown in fig. 1, the intelligent vehicle for article classification based on image recognition comprises a vehicle body, a mechanical arm 1 and a camera module 2 which are arranged on the vehicle body, a base of a tracked vehicle arranged at the bottom of the vehicle body and a control circuit 3 arranged on the vehicle body; wherein:
the camera module 2 is electrically connected with the control circuit 3 to realize information interaction;
the output end of the control circuit 3 is electrically connected with the mechanical arm 1 and the control end of the base of the tracked vehicle.
More specifically, a mechanical arm control module 11 and a digital steering engine 12 are arranged in the mechanical arm 1; wherein:
the input end of the mechanical arm control 11 module is electrically connected with the control circuit 3;
the output end of the mechanical arm control module 11 is electrically connected with the digital steering engine 12;
the digital steering engine 12 is used for driving the mechanical arm 1.
More specifically, the crawler base comprises crawler wheels, a direct current motor 4 and a frame; wherein:
two groups of crawler wheels and two groups of direct current motors 4 are arranged on the frame;
the frame is fixedly connected with the vehicle body;
the input end of the direct current motor 4 is electrically connected with the control circuit 3;
and the rotating shaft of the direct current motor 4 is fixedly connected with the rotating shaft of the crawler wheel.
More specifically, the control circuit 3 includes a microprocessor 31, a motor driving module 32 and a power supply module 33; wherein:
the microprocessor 31 is electrically connected with the camera module 2 to realize information interaction;
the microprocessor 31 is electrically connected with the input ends of the mechanical arm control module 11 and the motor driving module 32;
the output end of the motor driving module 32 is electrically connected with the direct current motor 4;
the power module 33 supplies power to the microprocessor 31 and the mechanical arm 1.
In the specific implementation process, the camera module 2 adopts an STM32H743VIT6 chip, and can realize the functions of characteristic identification such as color identification and shape identification, template matching, serial port communication and the like through programming control by python language, and the camera module has the advantages of small size, light weight, easy installation and low cost.
In the specific implementation process, the mechanical arm 1 with 6 degrees of freedom is adopted, and the mechanical arm 1 is driven to rotate by 6 digital steering engines 12 to complete the picking or placing action of the articles; the mechanical arm control module 11 adopts an STM32F103C8T6 chip, has 6 paths of PWM (pulse-width modulation) steering engine control signal output and serial port communication functions and the like, realizes the direct control of the mechanical arm 1 and the serial port communication function with the microprocessor 31, and programs through C language codes.
In the specific implementation process, the microprocessor 31 adopts an STM32F105RBT6 chip, has the functions of communicating between the motor driving module 32 and a serial port and the like, and is programmed by using C language codes.
Example 2
More specifically, on the basis of embodiment 1, the method for controlling the intelligent vehicle for classifying the articles based on image recognition comprises the following steps:
s1: initializing the intelligent trolley to enable the mechanical arm 1 to move to a standby state;
s2: driving the direct current motor 4 to drive the intelligent trolley to move and perform real-time scanning through the camera module 2 until the microprocessor 31 receives a parking signal;
s3: turning off the direct current motor 4 to stop the intelligent trolley from moving and carrying out real-time scanning by using the camera module 2 until the mechanical arm control module 11 receives a control signal;
s4: judging the type of the control signal, and if the type is 'pick up', executing step S5; if the "placement" is true, go to step S6;
s5: driving the robot arm 1 to pick up the article, moving the robot arm 1 to a standby state after the picking up is completed, sending an operation completion signal to the microprocessor 31, and executing step S7;
s6: driving the mechanical arm 1 to place articles, moving the mechanical arm 1 to a standby state after the placement is finished, and sending an operation completion signal to the microprocessor 31;
s7: the microprocessor 31 sends a next step identification instruction for the camera module 2 according to the operation completion signal type, and executes step S2.
More specifically, in step S2, the camera module 2 searches for a color patch in real time, and sends a parking signal to the microprocessor 31 when a color patch is found.
More specifically, in step S3, when the robot arm 1 holds an article, the camera module 2 identifies the placing position corresponding to the object through template matching and sends a "placing" signal to the microprocessor 31; when the arm 1 is not holding an article, the camera module 2 identifies the article position by shape color and sends a "pick up" signal to the microprocessor 31; the microprocessor 31 transmits the received signal to the robot arm control module 11.
More specifically, in step S5, the robot arm 1 moves to a standby state after completing the picking operation, and sends a "picking completion" signal to the microprocessor 31; in step S6, the robot arm 1 moves to a standby state after completing the placing operation, and sends a "placing completion" signal to the microprocessor 31.
More specifically, in step S7, when the microprocessor 31 receives the "pick-up completed" signal, it sends a template matching identification instruction to the camera module 2 to identify the corresponding placement position of the object; when the microprocessor 31 receives the "placement completion" signal, it sends a shape and color identification command to the camera module 2 to identify the position corresponding to the new article.
More specifically, the identification of color blocks is specifically divided and identified according to color threshold values corresponding to respective colors; the shape recognition adopts rapid edge detection, and the canny operator is utilized to realize the rapid edge detection and realize the shape recognition; and matching the template by utilizing an NCC template algorithm according to the recognized and shot image and the template picture to realize template matching.
In a specific implementation process, the mechanical arm 1 moves through the digital steering engine 13, and the mechanical principle is utilized to pick up and place articles; the control algorithm of the mechanical arm 1 adopts an interpolation algorithm, so that the mechanical arm 1 moves stably.
In the specific implementation process, the parameters related to color block identification comprise: threshold value of color, target area, area threshold value; the color threshold is a list which records a plurality of colors and is stored in the STM32H743VIT6 chip; the target region defines a region for analyzing the object patches so that the object appears at an intended location, such as the center of the field of view; the area threshold value is filtered if the framed area of the color blocks is smaller than the value, so that the shielding of the light or the background noise is realized.
In a specific implementation process, the shape recognition comprises circular recognition and rectangular recognition; distortion correction is needed before detection (a lens has a fish eye phenomenon), a circle is detected by Hough transform, and the radius and the center coordinates of the circle are returned; after distortion correction, a quaternion detection algorithm is used for identifying rectangles with any size and angle.
In a specific implementation process, the program flow of the camera module 2 specifically includes: when the intelligent vehicle starts to walk, color lumps are searched, a parking signal is sent to the microprocessor 31 only when the specified color lumps appear in the center of the visual field, the color and the shape of an object are identified, the corresponding signal is sent after the identification is completed, the mechanical arm 1 is clamped, then the picked signal is waited to return, template matching can be started after the signal is received, an area corresponding to the picked object is searched, a parking signal and a put-down signal can be sent to the microprocessor 31 after the identification is completed, then the put-down signal is waited to return, the step of starting color lump searching is carried out again after the signal is received, and the process is carried out in a circulating mode until the object is picked.
In the specific implementation process, the working process of the intelligent vehicle is as follows: when the intelligent vehicle runs, if the camera module 2 reaches an article, the camera module sends a signal to the microprocessor 31 through the serial port, and after the microprocessor 31 receives the signal, the direct current motor 4 is immediately stopped, so that the intelligent vehicle stops. The camera module 2 then identifies the item and, if the item is an item to be sorted, sends a signal to the microprocessor 31 to pick up. The microprocessor 31 receives the pick-up signal, and then sends the pick-up signal to the robot arm control module 11 through the serial port, and after the pick-up signal is received, the robot arm control module directly drives the robot arm 1 to pick up the object. After the mechanical arm 1 finishes working, the mechanical arm control module 11 sends a signal of completion of picking up to the microprocessor 31 through the serial port, and after the signal is received by the microprocessor, the microprocessor drives the direct current motor 4 to continue working, and simultaneously sends a signal of completion of picking up to the camera module 2 through the serial port, so that the camera module 2 starts to identify the classification destination. When the intelligent vehicle arrives at the destination where the intelligent vehicle is placed in a classified manner, the camera module 2 observes the destination identifier (which can be specific characters or specific objects), sends a stop signal to the microprocessor 31, and then the microprocessor 31 stops the direct current motor 4 to stop working, so that the intelligent vehicle stops. The camera module 2 recognizes the mark and sends a placing signal to the microprocessor 31 if the mark is the position where the article just picked up is to be placed. The microprocessor 31 then sends a placing signal to the robot arm control module 11, which, after receiving the signal, places the object that has just been picked up at the destination, and then sends a placing completion signal to the microprocessor 31. After receiving the signal, the microprocessor 31 sends a placement completion signal to the camera module 2, and simultaneously, the direct current motor 4 continues to work, and the intelligent vehicle continues to run. After receiving the placing completion signal, the camera module 2 starts a new round of object recognition.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
1. Article classification intelligence car based on image recognition, including the automobile body, its characterized in that: the crawler type automatic tracking vehicle further comprises a mechanical arm (1) and a camera module (2) which are arranged on the vehicle body, a crawler base which is arranged at the bottom of the vehicle body and a control circuit (3) which is arranged on the vehicle body; wherein:
the camera module (2) is electrically connected with the control circuit (3) to realize information interaction;
the output end of the control circuit (3) is electrically connected with the mechanical arm (1) and the control end of the base of the tracked vehicle.
2. The intelligent vehicle for classifying items based on image recognition according to claim 1, wherein: a mechanical arm control module (11) and a digital steering engine (12) are arranged in the mechanical arm (1); wherein:
the input end of the mechanical arm control module (11) is electrically connected with the control circuit (3);
the output end of the mechanical arm control module (11) is electrically connected with the digital steering engine (12);
the digital steering engine (12) is used for driving the mechanical arm (1).
3. The intelligent vehicle for classifying items based on image recognition according to claim 2, wherein: the crawler base comprises crawler wheels, a direct current motor (4) and a frame; wherein:
two groups of crawler wheels and two groups of direct current motors (4) are arranged on the frame;
the frame is fixedly connected with the vehicle body;
the input end of the direct current motor (4) is electrically connected with the control circuit (3);
and the rotating shaft of the direct current motor (4) is fixedly connected with the rotating shaft of the crawler wheel.
4. The intelligent vehicle for classifying items based on image recognition according to claim 3, wherein: the control circuit (3) comprises a microprocessor (31), a motor driving module (32) and a power supply module (33); wherein:
the microprocessor (31) is electrically connected with the camera module (2) to realize information interaction;
the microprocessor (31) is electrically connected with the mechanical arm control module (11) and the input end of the motor driving module (32);
the output end of the motor driving module (32) is electrically connected with the direct current motor (4);
the power module (33) supplies power to the microprocessor (31) and the mechanical arm (1).
5. The control method of the intelligent vehicle for classifying articles based on image recognition according to claim 4, wherein: the method comprises the following steps:
s1: initializing the intelligent trolley to enable the mechanical arm (1) to move to a standby state;
s2: driving a direct current motor (4) to enable the intelligent trolley to move and carry out real-time scanning through a camera module (2) until a microprocessor (31) receives a parking signal;
s3: the direct current motor (4) is turned off to stop the intelligent trolley from moving and real-time scanning is carried out by the camera module (2) until the mechanical arm control module (11) receives a control signal;
s4: judging the type of the control signal, and if the type is 'pick up', executing step S5; if the "placement" is true, go to step S6;
s5: driving the mechanical arm (1) to pick up the article, moving the mechanical arm (1) to a standby state after the picking up is finished, sending an operation completion signal to the microprocessor (31), and executing the step S7;
s6: driving the mechanical arm (1) to place articles, moving the mechanical arm (1) to a standby state after placing, and sending an operation completion signal to the microprocessor (31);
s7: the microprocessor (31) sends a next step identification instruction to the camera module (2) according to the operation completion signal type, and executes step S2.
6. The control method of the intelligent vehicle for classifying articles based on image recognition according to claim 5, wherein: in the step S2, the camera module (2) searches for a color patch in real time, and sends a parking signal to the microprocessor (31) when a color patch is found.
7. The control method of the intelligent vehicle for classifying articles based on image recognition according to claim 6, wherein: in the step S3, when the robot arm (1) holds an object, the camera module (2) identifies the placing position corresponding to the object through template matching and sends a "placing" signal to the microprocessor (31); when the mechanical arm (1) does not hold an article, the camera module (2) identifies the position of the article through shape and color and sends a pick-up signal to the microprocessor (31); the microprocessor (31) transmits the received signal to the robot arm control module (11).
8. The control method of the intelligent vehicle for classifying articles based on image recognition according to claim 7, wherein: in the step S5, the robot arm (1) moves to a standby state after completing the picking operation, and sends a "picking completion" signal to the microprocessor (31); in step S6, the robot arm (1) moves to a standby state after completing the placing operation, and sends a "placing completion" signal to the microprocessor (31).
9. The control method of the intelligent vehicle for classifying articles based on image recognition according to claim 8, wherein: in the step S7, when the microprocessor (31) receives the pickup completion signal, it sends a template matching identification instruction to the camera module (2) to identify the placing position corresponding to the object; when the microprocessor (31) receives the placing completion signal, a shape and color identification instruction is sent to the camera module (2) to identify the position corresponding to the new article.
10. The control method of the intelligent vehicle for classifying articles based on image recognition according to claim 9, wherein: the color block identification is divided and identified according to color threshold values corresponding to respective colors; the shape recognition adopts rapid edge detection, and the canny operator is utilized to realize the rapid edge detection and realize the shape recognition; and matching the template by utilizing an NCC template algorithm according to the recognized and shot image and the template picture to realize template matching.
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| CN111586363A (en) * | 2020-05-22 | 2020-08-25 | 深圳市百川安防科技有限公司 | Video file viewing method and system based on object |
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Application publication date: 20191220 |