Warehousing material automatic identification system

Abstract

The invention discloses a warehouse material automatic identification system, which comprises a material identification module, a positioning navigation module and a data management module, and is characterized in that the material identification module is used for carrying out image acquisition on materials on an AGV trolley and carrying out identification analysis so as to determine material information, and the positioning navigation module is used for monitoring the real-time position and the motion state of the AGV trolley in real time based on positioning equipment; and finally, based on system navigation, high-precision motion control is achieved, the data management module is used for data interaction between the material identification module and an external storage platform and data sharing and exchange between the positioning navigation module and the external storage platform, and the warehouse material automatic identification system is reasonable in design, simple in principle and high in practicability. The method has the following characteristics: 1, the accuracy and efficiency of material identification are improved, and manual intervention is reduced; 2, the utilization efficiency of the storage space is optimized, and the storage and extraction efficiency of the materials is improved; and 3, real-time transmission and sharing of information are realized, and the accuracy and timeliness of inventory management are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and in particular to an automatic identification system for warehouse materials. Background Art

[0002] With the rapid development of the logistics industry, the efficiency and accuracy of warehouse management have become crucial. Traditional warehouse material management methods have many problems, such as low accuracy and efficiency of manual material identification, prone to errors and omissions; low efficiency of warehouse space utilization, cumbersome material storage and retrieval process; untimely information transmission, resulting in chaotic inventory management, etc.

[0003] In order to solve these problems, various automation technologies are gradually applied to warehouse management. Among them, AGV, as a means of transportation that can move autonomously, plays an important role in warehouse logistics. However, the existing AGV still has some shortcomings in material recognition, such as low recognition accuracy and poor adaptability to complex environments.

[0004] In addition, with the continuous development of technologies such as the Internet of Things and artificial intelligence, the automatic identification system for warehouse materials also needs to be continuously innovated and improved to meet the growing logistics needs. Therefore, it is of great practical significance to develop an efficient and accurate automatic identification system for warehouse materials based on AGV recognition technology. Summary of the invention

[0005] The purpose of the present invention is to provide an automatic identification system for stored materials, which is based on AGV trolley identification technology and can realize automatic identification and management of stored materials, thereby improving the efficiency and accuracy of warehouse management.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The automatic identification system for storage materials is characterized by comprising a material identification module, a positioning navigation module and a data management module;

[0008] The material identification module: collects images of materials on the AGV, performs identification and analysis, and then determines the material information;

[0009] The positioning and navigation module monitors the real-time position and motion state of the AGV in real time based on the positioning device, and finally realizes high-precision motion control based on system navigation.

[0010] The data management module is used for data interaction between the material identification module, the positioning navigation module and the external storage platform to share and exchange data.

[0011] In the above-mentioned automatic identification system for stored materials, after acquiring the image of the material, the material identification module inputs it into the convolutional neural network, and the convolutional neural network performs multi-level feature extraction and abstraction on the image through continuous convolution, pooling and activation operations, thereby realizing the identification of the material;

[0012] The convolutional neural network is specifically:

[0013]

[0014] Among them, I is the input image information, F l is the lth layer feature map of the convolutional neural network, W l is the convolution kernel, b l is the bias term, F l+1 is the l+1th layer feature map obtained by convolution operation, f is the activation function, and n is the number of input feature maps.

[0015] In the above-mentioned automatic identification system for stored materials, the positioning and navigation module obtains the position and motion state information of the AGV in real time through the positioning device, and inputs this information into the positioning analysis algorithm for processing. The positioning analysis algorithm makes the best estimate of the position and motion state of the vehicle based on the observed value and the system model, and feeds the estimation result back to the system navigation, thereby completing the high-precision motion control of the AGV through the system navigation;

[0016] The positioning analysis algorithm is specifically:

[0017] x k|k =x k|k-1 +K k (z k -H k x k|k-1 );

[0018] P k|k =(LK k H k ) k|k-1 ;

[0019]

[0020] Among them, x k|k represents the optimal estimate of the system state at time t, P k|k represents the covariance matrix of the estimation error, z k represents the observed value, H k represents the observation matrix, R k represents the covariance matrix of the observation noise, and L represents the identity matrix.

[0021] In the above-mentioned automatic identification system for storage materials, the data management module uses a data encryption algorithm to encrypt sensitive data during data interaction to ensure data security; and uses a data compression algorithm to compress data and reduce data transmission volume and storage space; and verifies data through a data verification algorithm to ensure data integrity and accuracy; finally, the processed data is shared and exchanged between the material identification module, the positioning navigation module and the external storage platform through the data management module;

[0022] The data encryption algorithm is as follows:

[0023] C=E k (P)(encryption), P=D k (C) (decryption);

[0024] Among them, E k is the encryption function, D k is the decryption function, C is the ciphertext, and P is the plaintext.

[0025] The data compression algorithm uses the Huffman coding algorithm, which constructs a Huffman tree and assigns codes to characters according to the frequency of their occurrence:

[0026] The data verification algorithm is specifically as follows:

[0027]

[0028] Among them, d i is the data bit to be checked, C i is the i-th coefficient of the generator polynomial.

[0029] Technical effects and advantages of the present invention:

[0030] The present invention discloses a storage material automatic identification system, comprising a material identification module, a positioning and navigation module and a data management module. The material identification module collects images of materials on an AGV trolley, performs identification and analysis, and further determines material information. The positioning and navigation module monitors the real-time position and motion state of the AGV trolley in real time based on a positioning device, and finally realizes high-precision motion control based on system navigation. The data management module is used for data interaction between the material identification module, the positioning and navigation module and an external storage platform, and for data sharing and exchange. The storage material automatic identification system of the present invention is reasonably designed, simple in principle, and has the following characteristics: 1. It improves the accuracy and efficiency of material identification and reduces manual intervention; 2. It optimizes the utilization efficiency of storage space and improves the storage and extraction efficiency of materials; 3. It realizes real-time transmission and sharing of information and improves the accuracy and timeliness of inventory management. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] This embodiment discloses a storage material automatic identification system, including a material identification module, a positioning navigation module and a data management module;

[0033] The material identification module: collects images of materials on the AGV, performs identification and analysis, and then determines the material information;

[0034] The positioning and navigation module monitors the real-time position and motion state of the AGV in real time based on the positioning device, and finally realizes high-precision motion control based on system navigation.

[0035] The data management module is used for data interaction between the material identification module, the positioning navigation module and the external storage platform to share and exchange data.

[0036] In the above-mentioned automatic identification system for stored materials, after acquiring the image of the material, the material identification module inputs it into the convolutional neural network, and the convolutional neural network performs multi-level feature extraction and abstraction on the image through continuous convolution, pooling and activation operations, thereby realizing the identification of the material;

[0037] The convolutional neural network is specifically:

[0038]

[0039] Among them, I is the input image information, F l is the lth layer feature map of the convolutional neural network, W l is the convolution kernel, b l is the bias term, F l+1 is the l+1th layer feature map obtained by convolution operation, f is the activation function, and n is the number of input feature maps;

[0040] Compared with the existing conventional technology, the material recognition of the present invention is based on convolutional neural network, which has the characteristics of automatic learning of images. At the same time, it can perform multi-level feature extraction, which is suitable for the recognition of materials of different types and forms, and has high recognition accuracy and few missed judgments.

[0041] In the above-mentioned automatic identification system for stored materials, the positioning and navigation module obtains the position and motion state information of the AGV in real time through the positioning device, and inputs this information into the positioning analysis algorithm for processing. The positioning analysis algorithm makes the best estimate of the position and motion state of the vehicle based on the observed value and the system model, and feeds the estimation result back to the system navigation, thereby completing the high-precision motion control of the AGV through the system navigation;

[0042] The positioning analysis algorithm is specifically:

[0043] x k|k =x k|k -1+K k (z k -H k x k|k-1 );

[0044] P k|k =(LK k H k ) k|k-1 ;

[0045]

[0046] Among them, x k|k represents the optimal estimate of the system state at time t, P k|k represents the covariance matrix of the estimation error, z k represents the observed value, H k represents the observation matrix, R k represents the covariance matrix of the observation noise, and L represents the identity matrix;

[0047] Compared with existing conventional technologies, the positioning navigation of the present invention is based on a positioning analysis algorithm, which can more accurately determine the position and motion state of the AGV vehicle, provide a basis for high-precision control navigation, and at the same time achieve more intelligent motion control to improve efficiency and safety.

[0048] In the above-mentioned automatic identification system for storage materials, the data management module uses a data encryption algorithm to encrypt sensitive data during data interaction to ensure data security; and uses a data compression algorithm to compress data and reduce data transmission volume and storage space; and verifies data through a data verification algorithm to ensure data integrity and accuracy; finally, the processed data is shared and exchanged between the material identification module, the positioning navigation module and the external storage platform through the data management module;

[0049] The data encryption algorithm is as follows:

[0050] C=E k (P)(encryption), P=Dk (C) (decryption);

[0051] Among them, E k is the encryption function, D k is the decryption function, C is the ciphertext, and P is the plaintext.

[0052] The data compression algorithm uses the Huffman coding algorithm, which constructs a Huffman tree and assigns codes to characters according to the frequency of their occurrence:

[0053] The data verification algorithm is specifically as follows:

[0054]

[0055] Among them, d i is the data bit to be checked, C i is the i-th coefficient of the generator polynomial.

[0056] In the description of the present invention, unless otherwise clearly specified and limited, the terms "set", "install", "connect", "connect", and "fix" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0057] The standard parts used in the present invention can all be purchased from the market, and the special-shaped parts can all be customized according to the description in the specification.

[0058] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The automatic identification system for stored materials is characterized by: Including material identification module, positioning navigation module and data management module; The material identification module: collects images of materials on the AGV, performs identification and analysis, and then determines the material information; The positioning and navigation module: monitors the real-time position and motion state of the AGV car in real time based on the positioning device, and finally realizes high-precision motion control based on system navigation. The data management module is used for data interaction between the material identification module, the positioning navigation module and the external storage platform to share and exchange data.

2. The automatic identification system for stored materials according to claim 1 is characterized in that: After acquiring the image of the material, the material recognition module inputs it into the convolutional neural network. The convolutional neural network performs multi-level feature extraction and abstraction on the image through continuous convolution, pooling and activation operations, thereby realizing the recognition of the material.

3. The automatic identification system for stored materials according to claim 2 is characterized in that: The convolutional neural network is specifically: Among them, I is the input image information, F l is the lth layer feature map of the convolutional neural network, W l is the convolution kernel, b l is the bias term, F l+1 is the l+1th layer feature map obtained by convolution operation, f is the activation function, and n is the number of input feature maps.

4. The automatic identification system for stored materials according to claim 1 is characterized in that: The positioning and navigation module obtains the position and motion status information of the AGV car in real time through the positioning device, and inputs this information into the positioning analysis algorithm for processing. The positioning analysis algorithm makes the best estimate of the position and motion state of the car based on the observation value and the system model, and feeds the estimation result back to the system navigation, thereby completing the high-precision motion control of the AGV car through the system navigation.

5. The automatic identification system for stored materials according to claim 4 is characterized in that The positioning analysis algorithm is specifically: x k|k =x k|k-1 +K k (z k -J k x k|k-1 ); P k|k =(L-K k H k )P k|k-1 ; Among them, x k|k represents the optimal estimate of the system state at time t, P k|k represents the covariance matrix of the estimation error, z k represents the observed value, H k represents the observation matrix, R k represents the covariance matrix of the observation noise, and L represents the identity matrix.

6. The automatic identification system for stored materials according to claim 1 is characterized in that: During the data interaction process, the data management module uses a data encryption algorithm to encrypt sensitive data to ensure data security; and uses a data compression algorithm to compress data and reduce data transmission volume and storage space; In addition, the data is verified through a data verification algorithm to ensure the integrity and accuracy of the data; finally, the processed data is shared and exchanged between the material identification module, the positioning navigation module and the external warehousing platform through the data management module.

7. The automatic storage material identification system according to claim 6 is characterized in that: The specific data encryption algorithm is: C=E k (P)(encryption), P=D k (C) (decryption); Among them, E k is the encryption function, D k is the decryption function, C is the ciphertext, and P is the plaintext.

8. The automatic identification system for stored materials according to claim 6 is characterized in that: The data compression algorithm uses the Huffman coding algorithm, which constructs a Huffman tree and assigns codes to characters according to the frequency of their occurrence.

9. The automatic identification system for stored materials according to claim 6, characterized in that: The specific data verification algorithm is: Among them, d i is the data bit to be checked, C i is the i-th coefficient of the generator polynomial.

Images