Cooperative control method based on multiple autonomous mining trucks

Abstract

The present invention relates to the technical field of data transmission, in particular to a cooperative control method based on multiple autonomous mining trucks. The method comprises: according to a coding dictionary, performing maximum matching on a road condition data sequence, so as to acquire a current coding object and a matching serial number of the current coding object; according to the length of the coding dictionary, acquiring a first alternative coding length of the current coding object, and according to the first alternative coding length, acquiring coding results to be selected; according to the first alternative coding length and said coding results, acquiring a first coding result; acquiring a coding result on the basis of a second coding result of the current coding object, updating the coding dictionary, and performing continuous iteration to obtain compressed data; a cooperative control center decompressing the compressed data; and modeling road conditions, and broadcasting road condition information to all autonomous mining trucks, so as to perform cooperative control. The present invention achieves high compression efficiency for road condition images, ensures the real-time performance of road condition image transmission and improves the cooperative efficiency of autonomous mining trucks.

Description

Collaborative control method based on multiple unmanned mining vehicles Technical Field

[0001] The present invention relates to the field of data transmission technology, and in particular to a collaborative control method based on multiple unmanned mining vehicles. Background Art

[0002] Mines are dangerous working environments with a high risk of accidents. Collaborative control of multiple unmanned mining vehicles can reduce the risk of accidents and improve the efficiency of individual mining vehicles.

[0003] Unmanned mining vehicles need to transmit collected road condition data to a collaborative control center. The collaborative control center uses this data to model real-time road conditions and control the operation of the unmanned mining vehicles. To ensure the real-time nature of collaborative control, the road condition data must be compressed and transmitted.

[0004] Currently, traffic condition data is usually compressed using LZ coding. However, LZ coding is limited by the size of the coding dictionary, and its compression efficiency is limited, which affects the real-time transmission of traffic condition data and the efficiency of collaborative control.

[0005] Summary of the Invention

[0006] In order to solve the above problems, the present invention provides a collaborative control method based on multiple unmanned mining vehicles, which includes the following steps:

[0007] Collect road condition images and convert them into road condition data sequences; build an empty encoding dictionary and set the elements to be matched;

[0008] The road condition data sequence is encoded according to the encoding dictionary and the element to be matched, including: performing the longest match on the road condition data sequence starting from the element to be matched according to the encoding dictionary, obtaining a current encoding object and a matching sequence number of the current encoding object according to the matching result; obtaining a first candidate encoding length of the current encoding object according to the length of the encoding dictionary; obtaining a to-be-selected encoding result according to the first candidate encoding length; obtaining a first encoding result of the current encoding object according to the first candidate encoding length and the to-be-selected encoding result; obtaining a second encoding result of the current encoding object; obtaining an encoding result of the current encoding object according to the first encoding result and the second encoding result, and updating the encoding dictionary;

[0009] Set a new element to be matched, and repeat the encoding operation on the traffic data sequence according to the updated encoding dictionary and the new element to be matched until all elements in the traffic data sequence have been traversed, and stop the iteration, and obtain the compressed data according to the final encoding dictionary;

[0010] The compressed data is transmitted to the collaborative control center, and the compressed data is decompressed to obtain a road condition image; the collaborative control center performs real-time road condition modeling based on the road condition image, and broadcasts the road condition information to all unmanned mining vehicles to achieve collaborative control of multiple unmanned mining vehicles.

[0011] Preferably, the obtaining of the current coding object and the matching sequence number of the current coding object according to the matching result includes the following specific steps:

[0012] When there is no matching result, the element to be matched is used as the current coding object, and 0 is used as the matching sequence number of the current coding object; when there is a matching result, the matching result and its next element in the road condition data sequence are spliced ​​together as the current coding object, and the sequence number of the coding object matched by the matching result in the coding dictionary is used as the matching sequence number of the current coding object.

[0013] Preferably, the obtaining of the first candidate encoding length of the current encoding object according to the length of the encoding dictionary includes the following specific steps:

[0014] Wherein, N is the first candidate encoding length of the current encoding object; L is the length of the encoding dictionary when encoding the current encoding object; is the rounding symbol; max() is the maximum value function.

[0015] Preferably, the step of obtaining the selected encoding result according to the first candidate encoding length includes the following specific steps:

[0016] The first candidate code length is subtracted by 1 to obtain the second candidate code length, which is recorded as M. The matching sequence number of the current coding object is converted into a binary number of length M as the candidate coding result.

[0017] Preferably, the obtaining of the first encoding result of the current encoding object according to the first candidate encoding length and the encoding result to be selected includes the following specific steps:

[0018] When the first candidate code length N=1 or N=2, convert the matching sequence number of the current coding object into a binary number of length N as the first coding result of the current coding object;

[0019] When the length of the first alternative code N is greater than 2, a binary digit 0 is added to the end of the to-be-selected coding result, and the result is converted into a decimal number, which is recorded as the minimum extension value of the to-be-selected coding result; when the minimum extension value is greater than the length of the coding dictionary, the to-be-selected coding result is used as the first coding result of the current coding object; when the minimum extension value is less than or equal to the length of the coding object, the matching sequence number of the current coding object is converted into a binary number of length N, which is used as the first coding result of the current coding object.

[0020] Preferably, the obtaining of the second encoding result of the current encoding object includes the following specific steps:

[0021] The last element in the current encoding object is used as the suffix of the current encoding object; all encoding objects are obtained, the suffixes of all encoding objects are encoded with variable length, and the encoding results are used as the second encoding result of each encoding object.

[0022] Preferably, the step of obtaining the encoding result of the current encoding object according to the first encoding result and the second encoding result and updating the encoding dictionary includes the following specific steps:

[0023] The first encoding result and the second encoding result of the current encoding object are concatenated together as the encoding result of the current encoding object; the current encoding object and the encoding result of the current encoding object are added to the end of the encoding dictionary to implement the updating of the encoding dictionary.

[0024] Preferably, the step of obtaining compressed data according to the final encoding dictionary includes the following specific steps:

[0025] All encoding results in the final encoding dictionary are concatenated in order as compressed data.

[0026] Preferably, the setting of the elements to be matched includes the following specific steps:

[0027] The first element in the traffic data sequence is used as the element to be matched.

[0028] Preferably, the step of setting a new element to be matched includes the following specific steps:

[0029] The next element of the current encoding object in the traffic data sequence is used as a new element to be matched.

[0030] The beneficial effects of the technical solution of the present invention are as follows: the present invention performs the longest match on the road condition data sequence according to the coding dictionary, obtains the current coding object and the matching sequence number of the current coding object, obtains the first alternative coding length of the current coding object according to the length of the coding dictionary, obtains the to-be-selected coding result according to the first alternative coding length, and obtains the first coding result according to the first alternative coding length and the to-be-selected coding result. The present invention adaptively converts each matching sequence number into the length of a binary number according to the size of the dictionary during the coding process, so that the length of the binary number corresponding to the matching sequence number (i.e., the first coding result) is as small as possible, thereby improving the compression efficiency of the road condition image, ensuring the real-time transmission of the road condition image, and improving the collaborative efficiency of the unmanned mining vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] FIG1 is a flowchart of the steps of the collaborative control method based on multiple unmanned mining vehicles of the present invention;

[0033] FIG2 is a schematic diagram of a coding dictionary in the present invention;

[0034] FIG3 is a schematic diagram of the encoding dictionary in LZ encoding. DETAILED DESCRIPTION

[0035] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of the collaborative control method for multiple unmanned mining vehicles proposed by the present invention. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0036] Traditional LZ encoding achieves compression by updating the encoding dictionary while compressing. The encoding dictionary is used to perform the longest match on the data. The longest match result and the next character in the data are used as the encoding object. After the matching sequence number of the longest match result is converted to a binary number, it is combined with the encoding of the next character in the data as the encoding result of the encoding object. To ensure decodability, the matching sequence number needs to be converted to a fixed length when it is converted to a binary number. This length is determined by the largest sequence number in the final encoding dictionary. Since the final encoding dictionary is large, the largest sequence number is also large, which in turn makes the length of each matching sequence number converted to a binary number longer. This limits the compression efficiency of LZ encoding, affects the real-time transmission of road condition images, and leads to low collaborative efficiency of unmanned mining vehicles.

[0037] To this end, an embodiment of the present invention proposes a collaborative control method based on multiple unmanned mining vehicles. By adaptively converting the length of each matching sequence number into a binary number according to the size of the dictionary during the encoding process, the length of the binary number corresponding to each matching sequence number is made as small as possible, thereby improving the compression efficiency of LZ coding for road condition images, ensuring the real-time transmission of road condition images, and improving the collaborative efficiency of unmanned mining vehicles.

[0038] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0039] The specific scheme of the collaborative control method based on multiple unmanned mining vehicles provided by the present invention is described in detail below with reference to the accompanying drawings.

[0040] Please refer to FIG1 , which shows a flowchart of a collaborative control method based on multiple unmanned mining vehicles according to an embodiment of the present invention. The method includes the following steps:

[0041] S001. Collect road condition images.

[0042] In an embodiment of the present invention, a camera deployed on an unmanned mining vehicle is used to capture images of road conditions around the unmanned mining vehicle in real time.

[0043] S002. Compress the road condition image.

[0044] It should be noted that LZ encoding compresses while updating the coding dictionary, and decoding also updates the coding dictionary while decoding. Therefore, when encoding and decoding the same coded object, the corresponding coding dictionary is consistent. Therefore, the embodiment of the present invention sets the length of the binary number converted from the matching sequence number based on the size of the coding dictionary during the encoding process, making the length as short as possible, thereby improving the compression efficiency of LZ encoding, ensuring the real-time transmission of road condition images, and improving the collaborative efficiency of unmanned mining vehicles. During decoding, a binary number of the corresponding length is obtained based on the size of the coding dictionary. Converting the binary number to a decimal number can achieve decoding of the matching sequence number, and thus decoding of the coded object.

[0045] In the embodiment of the present invention, the grayscale values ​​of all pixels in the road condition image are expanded into a one-dimensional sequence as a road condition data sequence. The road condition data sequence is compressed as follows:

[0046] 1. Construct an empty encoding dictionary, which contains a sequence number column, an encoding object column, and an encoding result column. The encoding object column is used to store the encoding objects in the road condition data sequence, and the encoding result column is used to store the encoding results of the encoding objects.

[0047] 2. Take the first element in the traffic data sequence as the element to be matched.

[0048] 3. Perform the longest match on the road condition data sequence starting from the element to be matched based on all the coding objects contained in the coding dictionary. If no matching result exists, the element to be matched is used as the current coding object, and 0 is used as the matching sequence number of the current coding object. If a matching result exists, the matching result and the next element in the road condition data sequence are concatenated together as the current coding object, and the sequence number of the coding object matched by the matching result in the coding dictionary is used as the matching sequence number of the current coding object.

[0049] Get the length L of the encoding dictionary at this time, and get the first candidate encoding length of the current encoding object based on the length L of the encoding dictionary:

[0050] Wherein, N is the first candidate encoding length of the current encoding object; L is the length of the encoding dictionary when encoding the current encoding object; is the rounding symbol; max() is the maximum value function, and max(L+1,2) means taking the maximum value between L+1 and 2. The purpose is to prevent the result from being unable to be obtained or the result from being 0 when the length of the coding dictionary is 0 or 1. When the length of the coding dictionary is 0 or 1, the length of the first alternative code is 1, which ensures that when the matching sequence number is 0 or 1, it can be converted into a binary number with a length of 1 to represent it. When N is less than When all the serial numbers in the encoding dictionary cannot be used with a length of If N is expressed as a binary number, it will result in the inability to determine the length of the binary number corresponding to the current matching number during decoding, and thus the inability to decode the current matching number; when N is greater than When all serial numbers in the encoding dictionary are available with a length of , but most of them are of length The binary number has no corresponding serial number in the encoding dictionary, resulting in a lot of bit waste; It ensures that when the matching sequence number is any sequence number in the encoding dictionary, it can be converted into length It can be represented by a binary number without wasting many bits.

[0051] It should be noted that, for partially matched sequence numbers, the length of the converted binary number can be further reduced, thereby further reducing the number of coding bits and improving the transmission efficiency of the road condition image.

[0052] In the embodiment of the present invention, when the first candidate code length N=1 or N=2, the matching sequence number of the current coding object is converted into a binary number with a length of N as the first coding result of the current coding object.

[0053] When the length of the first candidate code N is greater than 2, the first candidate code length is subtracted by 1 to obtain the second candidate code length, recorded as M. The matching sequence number of the current encoding object is converted into a binary number of length M, which is recorded as the candidate code result. The binary digit 0 is added to the end of the candidate code result, and the result is converted to a decimal number, which is recorded as the minimum extension value of the candidate code result.

[0054] It should be noted that when the minimum expansion value is greater than the current encoding dictionary length L, if the candidate encoding result is used as the first encoding result of the current encoding object, and an N-bit binary number is read during decoding, the decimal number corresponding to the N-bit binary number does not exist in the sequence number column of the encoding dictionary. In this case, it can be known that the length of the first encoding result is M = N-1 bits. Reading an M-bit binary number during decoding can achieve decoding of the matching sequence number of the current encoding object. In this case, the candidate encoding result does not affect decoding, and the candidate encoding result can be directly used as the first encoding result of the current encoding object, thereby further reducing the number of encoding bits, improving compression efficiency, and improving the transmission efficiency of road condition data. When the minimum expansion value is less than the current encoding dictionary length L, if the candidate encoding result is used as the first encoding result of the current encoding object, and an N-bit binary number is read during decoding, and the decimal number corresponding to the N-bit binary number exists in the sequence number column of the encoding dictionary and is inconsistent with the matching sequence number corresponding to the candidate encoding result, this will cause a decoding error of the matching sequence number of the current encoding object, affecting decoding. In this case, the candidate encoding result cannot be directly used as the first encoding result of the current encoding object.

[0055] In an embodiment of the present invention, when the minimum extension value is greater than the length L of the encoding dictionary at this time, the selected encoding result is used as the first encoding result of the current encoding object; when the minimum extension value is less than or equal to the length L of the encoding object at this time, the matching sequence number of the current encoding object is converted into a binary number of length N as the first encoding result of the current encoding object.

[0056] The last element in the current encoding object is used as the suffix of the current encoding object. Since the suffix is ​​a grayscale value in the range [0, 255], the suffix is ​​converted into an 8-bit binary number as the second encoding result of the current encoding object.

[0057] In another embodiment, all encoding objects can be obtained first, and the suffixes of all encoding objects are encoded using variable-length encoding algorithms such as Huffman encoding and Shannon-Fanno encoding, and the encoding results are used as the second encoding results of each encoding object to further improve the compression efficiency.

[0058] The first encoding result and the second encoding result of the current encoding object are concatenated together to form the encoding result of the current encoding object. The current encoding object and the encoding result of the current encoding object are added to the encoding object column and the encoding result column of the last row of the encoding dictionary at this time, respectively, to implement the update of the encoding dictionary.

[0059] 4. The next element of the current encoding object in the traffic data sequence is used as a new element to be matched.

[0060] Repeat steps 3 and 4 until all elements in the traffic data sequence have been traversed, and then stop the iteration. All the encoding results of the encoding result column in the final encoding dictionary are concatenated in order as compressed data.

[0061] For example, when the traffic data sequence is {228, 176, 228, 87, 105, 228, 87, 176, 228, 87, 87, 176, 176, 105, 87}, the corresponding final encoding dictionary is shown in Figure 2, and the compressed data is 01110010000101100000101010111000011010011110110000110101011101010101100001000101010111. The road condition data sequence is compressed using existing LZ encoding to obtain the final encoding dictionary, as shown in Figure 3. The compressed data is 00001110010000001011000000010101011100000110100100111011000000110101010111001010110000010001010111. The compressed data in this embodiment of the present invention is 82 bits, while the compressed data obtained using LZ encoding is 96 bits. Compared with existing LZ encoding, this embodiment of the present invention has higher compression efficiency, ensures real-time transmission of road condition images, and improves the collaborative efficiency of unmanned mining vehicles.

[0062] At this point, the compressed data is obtained.

[0063] S003. Decompress the compressed data for transmission.

[0064] The compressed data is transmitted to the collaborative control center, which decompresses the compressed data transmitted by each unmanned mining vehicle:

[0065] 1. During the decompression process, a first candidate encoding length N is obtained according to the length of the encoding dictionary, N bits of binary data are read from the compressed data and converted into a decimal number. When the decimal number exists in the sequence number column in the encoding dictionary, the sequence number corresponding to the decimal number in the encoding dictionary is used as the matching sequence number; conversely, when the decimal number does not exist in the sequence number column in the encoding dictionary, M bits of binary data in the compressed data are read and converted into a decimal number, and the sequence number corresponding to the decimal number in the encoding dictionary is used as the matching sequence number.

[0066] 2. Continue to read 8-bit binary numbers in the compressed data as the second encoding result.

[0067] In another embodiment, a binary number is read from the compressed data using a decoding method in the Huffman coding algorithm as the second encoding result.

[0068] 3. Obtaining the current encoding object based on the matching sequence number and the second encoding result It should be noted that obtaining the current encoding object based on the matching sequence number and the second encoding result is a well-known technique in LZ encoding and will not be described in detail in the embodiments of the present invention.

[0069] 4. Repeat steps 1 to 3 until all bits in the compressed data have been traversed, and then stop iterating and use all the encoded objects obtained as the decompression results.

[0070] Restore the decompression result to a road condition image.

[0071] S004. The collaborative control center performs collaborative control of the unmanned mining vehicles.

[0072] The collaborative control center models the real-time road conditions based on the road condition images transmitted by multiple unmanned mining vehicles, and broadcasts the road condition information to all unmanned mining vehicles, controlling the unmanned mining vehicles to avoid obstacles in advance and cooperate with each other.

[0073] Through the above steps, the coordinated control of multiple unmanned mining vehicles is completed.

[0074] The embodiment of the present invention performs the longest match on the road condition data sequence according to the coding dictionary to obtain the current coding object and the matching sequence number of the current coding object, obtains the first alternative coding length of the current coding object according to the length of the coding dictionary, obtains the to-be-selected coding result according to the first alternative coding length, and obtains the first coding result according to the first alternative coding length and the to-be-selected coding result. The present invention adaptively converts each matching sequence number into the length of a binary number according to the size of the dictionary during the coding process, so that the length of the binary number corresponding to the matching sequence number (i.e., the first coding result) is as small as possible, thereby improving the compression efficiency of the road condition image, ensuring the real-time transmission of the road condition image, and improving the collaborative efficiency of the unmanned mining vehicle.

[0075] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A collaborative control method based on multiple unmanned mining vehicles, characterized in that: The method comprises the following steps: Collect road condition images and convert them into road condition data sequences; construct an empty encoding dictionary and set the elements to be matched; The road condition data sequence is encoded according to the encoding dictionary and the element to be matched, including: performing the longest match on the road condition data sequence starting from the element to be matched according to the encoding dictionary, and obtaining the current encoding object and the matching sequence number of the current encoding object according to the matching result; obtaining the first candidate encoding length of the current encoding object according to the length of the encoding dictionary; obtaining the encoding result to be selected according to the first candidate encoding length; obtaining the first encoding result of the current encoding object according to the first candidate encoding length and the encoding result to be selected; obtaining the second encoding result of the current encoding object; obtaining the encoding result of the current encoding object according to the first encoding result and the second encoding result, and updating the encoding dictionary; A new element to be matched is set, and the traffic condition data sequence is repeatedly encoded according to the updated encoding dictionary and the new element to be matched until all elements in the traffic condition data sequence have been traversed, and the iteration is stopped, and compressed data is obtained according to the final encoding dictionary; The compressed data is transmitted to the collaborative control center, and the compressed data is decompressed to obtain a road condition image; the collaborative control center performs real-time road condition modeling based on the road condition image, and broadcasts the road condition information to all unmanned mining vehicles to achieve collaborative control of multiple unmanned mining vehicles.

2. The collaborative control method based on multiple unmanned mining vehicles according to claim 1 is characterized in that: The specific steps of obtaining the current encoding object and the matching sequence number of the current encoding object according to the matching result are as follows: When there is no matching result, the element to be matched is used as the current coding object, and 0 is used as the matching sequence number of the current coding object; when there is a matching result, the matching result and its next element in the road condition data sequence are spliced ​​together as the current coding object, and the sequence number of the coding object matched by the matching result in the coding dictionary is used as the matching sequence number of the current coding object.

3. The collaborative control method based on multiple unmanned mining vehicles according to claim 1 is characterized in that: The step of obtaining the first candidate encoding length of the current encoding object according to the length of the encoding dictionary includes the following specific steps: Wherein, N is the first candidate encoding length of the current encoding object; L is the length of the encoding dictionary when encoding the current encoding object; is the rounding symbol; max() is the maximum value function.

4. The collaborative control method based on multiple unmanned mining vehicles according to claim 1 is characterized in that: The specific steps of obtaining the candidate encoding result according to the first candidate encoding length are as follows: The first candidate code length is subtracted by 1 to obtain the second candidate code length, which is recorded as M. The matching sequence number of the current coding object is converted into a binary number with a length of M as the candidate coding result.

5. The collaborative control method based on multiple unmanned mining vehicles according to claim 1 is characterized in that: The step of obtaining the first encoding result of the current encoding object according to the first candidate encoding length and the encoding result to be selected includes the following specific steps: When the length of the first candidate code is N=1 or N=2, the matching sequence number of the current coding object is converted into a binary number of length N as the first coding result of the current coding object; When the length of the first candidate code N>2, add a binary digit 0 to the end of the candidate code result, convert the result into a decimal number, and record it as the minimum extension value of the candidate code result; When the minimum extension value is greater than the length of the coding dictionary, the selected coding result is used as the first coding result of the current coding object; when the minimum extension value is less than or equal to the length of the coding object, the matching sequence number of the current coding object is converted into a binary number of length N as the first coding result of the current coding object.

6. The collaborative control method based on multiple unmanned mining vehicles according to claim 1 is characterized in that: The obtaining of the second encoding result of the current encoding object comprises the following specific steps: The last element in the current encoding object is used as the suffix of the current encoding object; all encoding objects are obtained, the suffixes of all encoding objects are encoded with variable length, and the encoding results are used as the second encoding result of each encoding object.

7. The collaborative control method based on multiple unmanned mining vehicles according to claim 1 is characterized in that: The step of obtaining the encoding result of the current encoding object according to the first encoding result and the second encoding result and updating the encoding dictionary includes the following specific steps: The first encoding result and the second encoding result of the current encoding object are concatenated together as the encoding result of the current encoding object; the current encoding object and the encoding result of the current encoding object are added to the end of the encoding dictionary to implement the updating of the encoding dictionary.

8. The collaborative control method based on multiple unmanned mining vehicles according to claim 1 is characterized in that: The specific steps of obtaining compressed data according to the final encoding dictionary are as follows: All encoding results in the final encoding dictionary are concatenated in order as compressed data.

9. The collaborative control method based on multiple unmanned mining vehicles according to claim 1 is characterized in that: The specific steps of setting the element to be matched are as follows: The first element in the traffic data sequence is used as the element to be matched.

10. The collaborative control method based on multiple unmanned mining vehicles according to claim 1 is characterized in that: The specific steps of setting a new element to be matched are as follows: The next element of the current encoding object in the traffic data sequence is used as a new element to be matched.

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