CN111570292A - OpenCV-based automatic book sorting and shelving robot system for facial recognition - Google Patents
OpenCV-based automatic book sorting and shelving robot system for facial recognition Download PDFInfo
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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
- B07C3/00—Sorting according to destination
- B07C3/02—Apparatus characterised by the means used for distribution
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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
- B07C3/00—Sorting according to destination
- B07C3/10—Apparatus characterised by the means used for detection ofthe destination
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
- G06V10/462—Salient features, e.g. scale invariant feature transforms [SIFT]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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Abstract
The invention discloses an OpenCV-based automatic book sorting and shelving robot system for facial recognition. The invention relates to a robot for automatically sorting and putting books on a shelf in a library, which integrates the borrowing, returning, checking, classifying, putting books on and putting books off the shelf and the like. OpenCV-based facial recognition technology has been introduced to the borrowing or returning of books by readers. OpenCV is known throughout as the Open Source Computer Vision Library. OpenCV can easily handle image input and output of images, memory allocation and conversion, matrix operation, linear operation, support for various dynamic data structures, basic image processing work, structural analysis algorithm, camera calibration algorithm, motion analysis and visualization of target objects, image labeling, and the like.
Description
Technical Field
The invention belongs to a novel library service robot, and particularly relates to an OpenCV-based automatic facial recognition book sorting and shelving robot system. The automatic book sorting and shelving robot applies a facial recognition technology to a local or college library and can complete a series of works such as book borrowing, returning, inventory, classification, shelving and the like.
Background
With the rapid development of society and the demand of people for good life, the library becomes an important place for readers to make up for the deficiency and acquire knowledge in all aspects during the rest day after learning and working. Originally, reading time of readers is insufficient, and a lot of books are borrowed and returned in a traditional library or manually, so that a great amount of precious reading time is wasted in the aspects of book borrowing and returning of the readers.
Aiming at the problem, a face recognition technology is introduced into an automatic book sorting and shelving robot of a library to borrow and return books, and the library book borrowing and returning efficiency is greatly improved. In order to avoid book returning retention and influence on borrowing of readers, the automatic book sorting and shelving robot in the library is designed to be capable of completing work of book misplacing, carrying, classifying, checking, shelving and the like, so that labor consumption is reduced, and work efficiency is improved.
Disclosure of Invention
The purpose of the invention is as follows: in order to solve the defects of the prior art, the invention provides an OpenCV-based automatic book sorting and shelving robot system for face recognition.
The technical scheme is as follows: an OpenCV-based automatic book sorting and shelving robot system for facial recognition comprises a sliding device, wherein an upper computer adopts a raspberry group, a book distribution device, a book clamping device, a mobile body driving device and a book storage cabinet;
the sliding devices are respectively arranged at two sides of the bookcase, and each sliding device consists of a group of 85H2P11860A4 stepping motors, an elastic coupling, a bearing, a ball screw, a sliding block and a guide rail; the up-and-down movement of the sliding block is controlled through the forward and reverse rotation of the stepping motor;
the book dividing device and the book clamping device are respectively arranged on the sliding block and comprise a mechanical arm, a mechanical claw and a depth camera; two servo motors are arranged between joints of the mechanical arm respectively to control the mechanical arm to rotate, and each mechanical arm is provided with six servo motors;
a mechanical claw 18 consisting of two steel sheets is arranged at the front end of the three-joint mechanical arm 16, the mechanical claw 18 is in a hook shape, the closed mechanical claw has 25 degrees, the sharp angle is convenient to insert into a gap between books, the insertable gap is 0.8mm, and the steel sheets are made of heat-treated 45# steel;
the mechanical claw 19 is different from the mechanical claw 18 in structure, is directly composed of two steel plates, is mainly used for book taking and clamping, and places books into a space opened by the mechanical claw 18;
the depth camera can perform 3D modeling on the books on the bookshelf to acquire three-dimensional information of the books, so that the speed and the precision of identifying the book searching number are improved, and the books are placed on the shelf more accurately;
the moving body driving device consists of an ultrasonic obstacle avoidance module, two driving wheels and two universal wheels; the two driving wheels and the two universal wheels respectively control the whole robot to keep linear and steering motion in the library; the ultrasonic obstacle avoidance module and the two-dimension code recognition module arranged at the bottom of the mobile body driving device read the information of the ground two-dimension code, determine the real-time position of the robot and realize autonomous navigation;
the book storage cabinet is divided into four layers, the first layer is standby, returned books are placed in the third layer, due to the fact that the book placing mode of the book shelf in the library cannot be changed on a large scale, enough space is set in each layer to place each book, enough space is reserved between the books and the books, the mechanical claw can directly grab the books after information of the books on the shelf is obtained, and the mechanical claw is prevented from being used for separating the books.
As an optimization: the controller circuit structure of the automatic book sorting and shelving robot system mainly comprises a controller module, a camera acquisition module, a motion control module and a wireless communication module; wherein, MCU1 is the motion treater, MCU2 is for borrowing the system's treater of returning, the data transmission and the processing of each module of CPU control, camera 1 and camera 2 are used for confirming the position of writing for dividing the book device and pressing from both sides the book device collection books information respectively, camera 3 discerns the two-dimensional code information on ground, realize autonomic location, camera 4 carries out face information acquisition and facial recognition, RFID technique is used for scanning the bar code on the book and returns the book, the transmission of above data all goes on through the ethernet mode.
As an optimization: the method comprises the steps that a reader contacts an administrator to collect facial information before borrowing books, the administrator stores the collected facial information into a library facial database, when the reader borrows or returns books, only the human faces and book bar codes are displayed in front of a camera, the camera compares the detected facial information with the human faces in the database through collection, and after the identification is successful, the borrowed or returned books are added or deleted in a personal information base.
A working method of the robot system for automatically sorting and shelving books according to the OpenCV-based face recognition book is characterized in that the specific control process of book shelving is as follows:
after a reader returns books to a book storage cabinet through facial recognition, and when the number of the returned books reaches a certain number, the book shelf loading robot starts automatic shelf loading work;
firstly, a book clamping device is started, a sliding block drives a mechanical arm to move up and down on a guide rail to determine the number of layers of a book cabinet where books to be put on a shelf are located, the mechanical arm drives each joint to move, and after book information is acquired through left-right rotation of a depth camera arranged at the front end of the mechanical arm, a mechanical claw acts to clamp the books to be put on the shelf;
then the movable body driving device drives the two driving wheels and the two universal wheels to move to reach the bookshelf position, the book distribution device is started, the sliding block drives the mechanical arm to move up and down on the guide rail to determine the position of the books on the bookshelf, the mechanical arm drives each joint to move towards the target bookshelf, and the information of the books is obtained through the left-right rotation of the depth camera arranged at the front end of the mechanical arm;
after the position of the book to be returned is determined, the mechanical claw 18 is inserted into the gap and opened to obtain enough space, the mechanical claw 19 puts the clamped book into the space, and the mechanical arm retracts;
and repeating the steps to carry out shelving work of the next book until all books in the book cabinet are placed on shelves, and moving the body driving device to drive the two driving wheels and the two universal wheels to return to the initial point.
Has the advantages that: the invention relates to a robot for automatically sorting and putting books on a shelf in a library, which integrates the borrowing, returning, checking, classifying, putting books on and putting books off the shelf and the like. OpenCV-based facial recognition technology has been introduced to the borrowing or returning of books by readers. OpenCV is known throughout as the Open Source computer Vision Library. OpenCV can easily handle image input and output of images, memory allocation and conversion, matrix operation, linear operation, support for various dynamic data structures, basic image processing work, structural analysis algorithm, camera calibration algorithm, motion analysis and visualization of target objects, image labeling, and the like.
Drawings
FIG. 1 is a schematic diagram showing the overall structure of an automatic book sorting and shelving robot system of the present invention;
FIG. 2 is a schematic diagram of the automatic book sorting and shelving robot system of the present invention;
FIG. 3 is an enlarged partial schematic view of the robotic arm of the present invention;
FIG. 4 is a schematic bottom view of the automatic book sorting and shelving robot of the present invention;
FIG. 5 is a schematic diagram of an AdaBoost face location detection process according to the present invention;
FIG. 6 is a block diagram of the robot controller circuit configuration of the present invention;
fig. 7 is a schematic illustration of the face recognition borrowing and returning process object display of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below so that those skilled in the art can better understand the advantages and features of the present invention, and thus the scope of the present invention will be more clearly defined. The embodiments described herein are only a few embodiments of the present invention, rather than all embodiments, and all other embodiments that can be derived by one of ordinary skill in the art without inventive faculty based on the embodiments described herein are intended to fall within the scope of the present invention.
Examples
The face recognition of the invention mainly comprises three parts of face detection, face characterization and face recognition. When people borrow or return books, the face images collected generally are all front faces, so that an Adaboost face detection algorithm is applied in face detection. The algorithm is based on an integral graph, a cascade detector and an Adaboost algorithm, can quickly detect the face on the front side, and is high in identification precision.
As shown in fig. 5, a schematic diagram of an AdaBoost face location detection process, an AdaBoost face detection algorithm is specifically implemented as follows:
A. inputting a training set (x)1,y1),(x2,y2),KK,(xi,yi),KK(xn,yn) Wherein x isiFor the ith sample, yiIs a sample object, yi∈ (0, 1), where 0, 1 respectively represent positive sample object and negative sample object, 0 can be regarded as non-face and 1 as face in face detection.
B. Initializing training sample weights D (i): in contrast to a positive sample target, the target,
(M is the total number of positive samples)
C. For T ═ 1,2, K, T, the following steps are performed cyclically:
1. normalization weight:
2. obtaining a characteristic value f in each training, wherein the characteristic value f has a weak classifier h (x, f, p, theta) corresponding to the characteristic value f; the weighted error rate of the weak classifier can be calculated by the following formula:
f＝∑iqi|h(xi,f,p,θ)-yi| (2)
3. according to the above calculation result, the minimum error rate is selectedfCorresponding weakest classifier hf(x) And continuing to calculate:
t＝minf,p,θ∑iqi|h(xi,f,p,θ)-yi|＝∑iqi|h(xi,ft,pt,θt)-yi| (3)
ht(x)＝h(xi,ft,pt,θt) (4)
4. update all sample weights:
5. finally, the strongest classifier is obtained
Wherein the content of the first and second substances,
6. and storing the training result.
That is to say, the reader contacts the administrator to collect the facial information before borrowing the book, the administrator stores the collected facial information into the library facial database, when the reader borrows or returns the book, the human face and the book bar code are only required to be presented before the camera, the camera compares the detected facial information with the human face in the database through collection, and after the identification is successful, the book to be borrowed or returned is added or deleted in the personal information base of the user.
After the books are returned, the robot classifies the books and puts the books on the shelf. As shown in fig. 6, the automatic book sorting and shelving robot controller circuit structure mainly comprises a controller module, a camera acquisition module, a motion control module, a wireless communication module and the like. MCU1 is the motion processor, MCU2 is for borrowing the system's treater of returning, the data transmission and the processing of each module of CPU control, camera 1 and camera 2 are respectively for dividing the book device and pressing from both sides the book device and gather books information and confirm the position of writing, camera 3 discerns the two-dimensional code information on ground, realize autonomic location, camera 4 carries out face information acquisition and facial recognition, RFID technique is used for scanning the bar code on the book and returns the book, the transmission of above data all goes on through the ethernet mode.
As shown in fig. 1-2, in the overall mechanical structure design of the automatic book sorting and shelving robot, the automatic book sorting and shelving robot is mainly divided into six parts, namely a sliding device 1, an upper computer 2 adopting a raspberry group, a book dividing device 3, a book clamping device 4, a movable body driving device 5 and a book storage cabinet 6.
The sliding devices are respectively arranged at two sides of the bookcase 6, each sliding device consists of a group of 85H2P11860A4 stepping motors 7 and 8, an elastic coupling, bearings 10 and 11, ball screws 12 and 13, sliding blocks 14 and 15 and guide rails 26 and 27, and the up-and-down movement of the sliding blocks 14 and 15 is controlled through the forward and reverse rotation of the stepping motors.
As shown in fig. 3, the book dividing device 3 and the book clamping device 4 are respectively mounted on the sliders 14 and 15 and comprise mechanical arms 16 and 17, mechanical claws 18 and 19 and depth cameras 20 and 21 respectively. Two servo motors are respectively arranged between joints of the mechanical arms 16 and 17 to control the rotation between the mechanical arms, and each mechanical arm is provided with six servo motors.
The mechanical claw 18 consisting of two steel sheets is arranged at the front end of the three-joint mechanical arm 16, the mechanical claw 18 is in a hook shape (as shown in figure 3), when the mechanical claw is closed, the angle is 25 degrees, the sharp angle (as shown in figure 4) is convenient to insert into a gap between books, the insertable gap is 0.8mm, the steel sheets are made of heat-treated 45# steel, and the hardness is high enough to support the pressure born in the book splitting process.
The gripper 19 is different from the gripper 18 in structure, is directly composed of two steel plates, and is mainly used for taking and clamping books and placing the books into a space opened by the gripper 18.
The depth cameras 20 and 21 can perform 3D modeling on books on the bookshelf to acquire three-dimensional information of the books, so that the speed and the precision of book searching number identification are improved, and the books are placed on shelves more accurately.
As shown in fig. 4, the moving body driving device 5 is composed of an ultrasonic obstacle avoidance module 22, two driving wheels 23, and two universal wheels 24. Two driving wheels 23 and two universal wheels 24 respectively control the whole robot to keep a straight line and a steering movement in the library. The ultrasonic obstacle avoidance module 22 and the two-dimension code recognition module 9 installed at the bottom of the mobile body driving device 5 read the information of the ground two-dimension code, determine the real-time position of the robot, and realize autonomous navigation. Store up book case 6 and divide into four layers (the first layer is reserve, books that return are placed to the back three-layer), because can not carry out extensive change to the books mode that library's bookshelf was placed, this research team has made further improvement to the robot stores up book case, we all set up sufficient space on each layer and place every book, have sufficient space between books and the books and let gripper 19 after the information of acquireing the books of putting on the shelf, can directly snatch books, avoid gripper 18 to go to this step of branch books again, save plenty of time, improve the work efficiency of robot.
The book shelf is also put on the shelf in a specific control process: after the reader returns the books to the book storage cabinet 6 through facial recognition, the book shelf robot starts automatic shelf-loading work after the returned books reach a certain number. Firstly, the book clamping device 4 is started, the slide block 15 drives the mechanical arm 17 to move up and down on the guide rail 27 to determine the number of layers of the book cabinet 6 on which books are put on shelf, the mechanical arm 17 drives each joint to move, and after book information is acquired by left and right rotation of the depth camera 21 arranged at the front end of the mechanical arm 17, the mechanical claw 19 acts to clamp the books to be put on shelf. Then the movable body driving device 5 drives the two driving wheels 23 and the two universal wheels 24 to move to reach the bookshelf position, the book distribution device 3 is started, the sliding block 14 drives the mechanical arm 16 to move up and down on the guide rail 26 to determine the position of the books on the bookshelf, the mechanical arm 16 drives each joint to move to point to the target bookshelf, and the depth camera 20 installed at the front end of the mechanical arm 16 rotates left and right to obtain book information. After the position of the book is determined, the gripper 18 is inserted into the slot and opened to obtain a sufficient space, the gripper 19 puts the clamped book into the space, and the robot arm retracts. Repeating the above steps, and carrying out the shelving work of the next book until all books in the book cabinet are put on shelves, and moving the body driving device 5 to drive the two driving wheels 23 and the two universal wheels 24 to return to the initial point.
The invention relates to a robot for automatically sorting and putting books on a shelf in a library, which integrates the borrowing, returning, checking, classifying, putting books on and putting books off the shelf and the like. OpenCV-based facial recognition technology has been introduced to the borrowing or returning of books by readers. OpenCV is known throughout as the Open Source computer Vision Library. OpenCV can easily handle image input and output of images, memory allocation and conversion, matrix operation, linear operation, support for various dynamic data structures, basic image processing work, structural analysis algorithm, camera calibration algorithm, motion analysis and visualization of target objects, image labeling, and the like.
Claims (4)
1. The utility model provides a facial recognition books automatic separation robot system that puts on shelf based on OpenCV which characterized in that: comprises a sliding device (1), an upper computer (2) adopts a raspberry group, a book dividing device (3), a book clamping device (4), a mobile body driving device (5) and a book storage cabinet (6);
the sliding devices (1) are respectively arranged on two sides of the bookcase (6), and each sliding device (1) consists of a group of 85H2P11860A4 stepping motors (7 and 8), an elastic coupling, bearings (10 and 11), ball screws (12 and 13), sliding blocks (14 and 15) and guide rails (26 and 27); the up-and-down movement of the sliding blocks (14, 15) is controlled by the positive and negative rotation of the stepping motors (7, 8);
the book dividing device (3) and the book clamping device (4) are respectively arranged on the sliding blocks (14, 15) and comprise mechanical arms (16, 17), mechanical claws (18, 19) and depth cameras (20, 21); two servo motors are respectively arranged between joints of the mechanical arms (16, 17) to control the rotation between the mechanical arms, and each mechanical arm is provided with six servo motors;
a mechanical claw (18) consisting of two steel sheets is arranged at the front end of the three-joint mechanical arm (16), the mechanical claw (18) is in a hook shape, the angle is 25 degrees when the mechanical claw is closed, the sharp angle is convenient to insert into a gap between books, the insertable gap is 0.8mm, and the steel sheets are made of heat-treated 45# steel;
the mechanical claw (19) and the mechanical claw (18) have different structures, are directly composed of two steel plates, are mainly used for book taking and clamping, and place books into a space opened by the mechanical claw (18);
the depth cameras (20 and 21) can perform 3D modeling on the books on the bookshelf to acquire three-dimensional information of the books, so that the speed and the precision of identifying the book searching number are improved, and the books are placed on the shelf more accurately;
the moving body driving device (5) consists of an ultrasonic obstacle avoidance module (22), two driving wheels (23) and two universal wheels (24); the two driving wheels (23) and the two universal wheels (24) respectively control the whole robot to keep linear and steering motion in a library; the ultrasonic obstacle avoidance module (22) and the two-dimension code recognition module (9) installed at the bottom of the mobile body driving device (5) read the information of the ground two-dimension code, determine the real-time position of the robot and realize autonomous navigation;
the book storage cabinet (6) is divided into four layers, the first layer is standby, returned books are placed in the last three layers, due to the fact that the book placing mode of the library bookshelf cannot be changed on a large scale, enough space is set for placing each book in each layer, enough space is reserved between the books and the mechanical claws (19) to enable the books to be directly grabbed after the information of the books on the shelf is obtained, and the step that the mechanical claws (18) are used for separating the books is avoided.
2. The OpenCV-based face recognition book auto-sorting shelving robot system of claim 1, wherein: the controller circuit structure of the automatic book sorting and shelving robot system mainly comprises a controller module, a camera acquisition module, a motion control module and a wireless communication module; wherein, MCU1 is the motion treater, MCU2 is for borrowing the system's treater of returning, the data transmission and the processing of each module of CPU control, camera 1 and camera 2 are used for confirming the position of writing for dividing the book device and pressing from both sides the book device collection books information respectively, camera 3 discerns the two-dimensional code information on ground, realize autonomic location, camera 4 carries out face information acquisition and facial recognition, RFID technique is used for scanning the bar code on the book and returns the book, the transmission of above data all goes on through the ethernet mode.
3. The OpenCV-based face recognition book auto-sorting shelving robot system of claim 2, wherein: the method comprises the steps that a reader contacts an administrator to collect facial information before borrowing books, the administrator stores the collected facial information into a library facial database, when the reader borrows or returns books, only the human faces and book bar codes are displayed in front of a camera, the camera compares the detected facial information with the human faces in the database through collection, and after the identification is successful, the borrowed or returned books are added or deleted in a personal information base.
4. An operating method of the OpenCV-based facial recognition book automatic sorting shelving robot system according to claim 1, wherein the operating method comprises the following steps: the book shelf control process is as follows:
after the readers return the books to the book storage cabinet (6) through facial recognition, and when the number of the returned books reaches a certain number, the book shelf-loading robot starts automatic and automatic shelf-loading work;
firstly, a book clamping device (4) is started, a sliding block (15) drives a mechanical arm (17) to move up and down on a guide rail (27) to determine the number of layers of a book storage cabinet (6) where books to be put on the shelf are located, the mechanical arm (17) drives each joint to move, and after book information is acquired through left-right rotation of a depth camera (21) arranged at the front end of the mechanical arm (17), a mechanical claw (19) acts to clamp the books to be put on the shelf;
then a moving body driving device (5) drives two driving wheels (23) and two universal wheels (24) to move to reach the bookshelf position, a book distribution device (3) is started, a sliding block (14) drives a mechanical arm (16) to move up and down on a guide rail (26) to determine the position of a book on the bookshelf, the mechanical arm (16) drives each joint to move to point to a target bookshelf, and book information is obtained through left-right rotation of a depth camera (20) arranged at the front end of the mechanical arm (16);
after the position of the book to be returned is determined, the mechanical claw (18) is inserted into the gap and opened to obtain enough space, the mechanical claw (19) puts the clamped book into the space, and the mechanical arm retracts;
repeating the steps, carrying out the shelving work of the next book until all the books in the book storage cabinet are put on shelves, and moving the body driving device (5) to drive the two driving wheels (23) and the two universal wheels (24) to return to the initial point.
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| CN112692839A (en) * | 2021-03-23 | 2021-04-23 | 佛山隆深机器人有限公司 | Book sorting method and device based on double-arm robot |
| CN112692839B (en) * | 2021-03-23 | 2021-08-24 | 佛山隆深机器人有限公司 | Book sorting method and device based on double-arm robot |
| RU210378U1 (en) * | 2021-11-02 | 2022-04-14 | Дмитрий Валерьевич Евстигнеев | AUTOMATED CONTROL DEVICE FOR LIBRARIES |
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