CN113450053A - Food material supply management method and system based on big data - Google Patents
Food material supply management method and system based on big data Download PDFInfo
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- CN113450053A CN113450053A CN202110753674.9A CN202110753674A CN113450053A CN 113450053 A CN113450053 A CN 113450053A CN 202110753674 A CN202110753674 A CN 202110753674A CN 113450053 A CN113450053 A CN 113450053A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The application relates to a food material supply management method and system based on big data, wherein the method comprises the following steps: acquiring current actual linear distance data between the robot main body and the food material placing manipulator based on the robot main body and the motion monitoring transducer array; judging whether the current actual linear distance data is less than or equal to a preset mountable linear distance; if the distance is not smaller than or equal to the preset settleable straight line distance, generating settleable target path data based on the actual distance to be adjusted and the current actual straight line distance data, and judging whether the current actual straight line distance data is smaller than or equal to the preset settleable straight line distance. According to the food material arranging manipulator, food material management and arrangement can be carried out according to the current position, and data support for subsequent big data analysis can be realized by storing the arrangement process data based on big data.
Description
Technical Field
The present application relates to the technical field of food material supply management, and in particular, to a method and a system for food material supply management based on big data.
Background
With the development and progress of society, people have more and more strict requirements on food materials, so that higher requirements on food material management and supply are provided, and technical schemes for food material supply management are numerous, for example, in a patent document with the application number of CN201510946943.8, a method, a device and a system for intelligent management of food materials are disclosed. The method comprises the following steps: the intelligent management equipment detects the stored food materials to obtain food material names; the intelligent management equipment sends the food material name to a server so that the server obtains a menu according to the food material name, wherein the menu comprises the food material name; and the intelligent management equipment receives and displays the menu sent by the server so that a user can make dishes according to the menu.
Although the technical scheme can obtain the menu containing the food material name according to the food material name, the user can make the dish according to the menu, the user is prevented from continuously browsing the contents of the related menu in the book or the webpage in the process of actually cooking the dish, and the convenience is improved for the user; in addition, the food materials in the intelligent management equipment can be maximally utilized by the user. However, the existing food material arrangement management process is complicated, effective arrangement management of various food materials in a warehouse cannot be realized, accurate arrangement of the food materials in the warehouse cannot be realized, and the problem of low food material management efficiency exists.
Disclosure of Invention
In view of the above, there is a need to provide a method and a system for managing food supply based on big data, which can improve the efficiency of food placement and management processing.
The technical scheme of the invention is as follows:
a food material supply management method based on big data is based on a food material transportation robot, the food material transportation robot is arranged in a food material management warehouse, a plurality of food material arrangement points are arranged in the food material management warehouse, and each food material arrangement point is provided with a food material arrangement mechanical arm; the food material transportation robot comprises a robot main body, a motion monitoring transducer array, a position adjusting driving mechanism and a position adjusting transducer array; the top end of the robot main body is used for bearing food materials, and the motion monitoring transducer array is installed on the robot main body and used for acquiring motion information of the robot main body; the position adjusting driving mechanism is arranged on the robot main body, is also connected with the position adjusting transducer array and drives the position adjusting transducer array to move; the method comprises the following steps:
acquiring current actual linear distance data between the robot main body and the food material placing manipulator based on the robot main body and the motion monitoring transducer array; judging whether the current actual linear distance data is smaller than or equal to a preset settleable linear distance or not by a main control unit based on food preset by the food transport robot; if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained; generating placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, controlling the robot main body to move to a position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
Optionally, an image acquisition device is further installed in the food material management warehouse, and the image acquisition device is arranged in the food material management warehouse and is used for detecting and acquiring image information in the food material management warehouse;
if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained; the method specifically comprises the following steps: if the current actual linear distance data is judged to be not less than or equal to the preset mountable linear distance, acquiring current position image data of the position adjustment transducer array based on the image acquisition device, and sending the current position image data to the food material judgment main control unit; acquiring a current detectable trigger range detected by the position adjusting transducer array at a current position in the current position image data based on the position adjusting transducer array; judging whether the current detectable trigger range contains food materials borne by the robot main body and the farthest trigger range edge of the food material arranging manipulator or not; if the current detectable trigger range does not contain the food materials loaded on the robot main body and the farthest trigger range edge of the food material placing manipulator, generating a position driving adjustment instruction; based on the position driving adjustment instruction, the food material judgment main control unit controls the position adjustment driving mechanism to adjust the position adjustment transducer array to obtain the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator.
Optionally, step S400: generating settleable target path data based on the actual distance to be adjusted and the current actual linear distance data, judging a position where the robot main body moves and matches the settleable target path data through the food material, controlling the robot main body to move by the main control unit, generating settleable process data, and storing the settleable process data based on big data, wherein the settleable target path data specifically comprises the following steps:
based on the image acquisition device, in an obstruction area formed by taking the actual distance to be adjusted as a core, obstructing object image data which obstructs the robot main body to move to a triggerable range of the food material arranging manipulator; generating a plurality of passable path data according to the image data of the obstructing object, the actual distance to be adjusted and the current actual linear distance data; screening out the shortest route from the multiple passable route data, and setting the data corresponding to the route as placeable target route data; and controlling the robot main body to move to the position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
Optionally, still be provided with the robot of removing obstacles in the edible material management storehouse, through edible material judges the main control unit control the robot main part motion is in place for can settle target path data assorted position, and generate and settle process data, will settle process data is based on big data storage, specifically includes:
acquiring surrounding obstacle information in the placeable target path data in real time based on the motion monitoring transducer and the image acquisition device during the motion of the robot body; comparing the peripheral obstacle information respectively acquired by the motion monitoring transducer and the image acquisition device, and generating actual obstacle information; and sending the actual obstacle information to an obstacle removing robot, and controlling the obstacle removing robot to remove the obstacles contained in the actual obstacle information.
Optionally, the storing the installation process data based on big data specifically includes:
splitting the installation process data into a plurality of thinning process data according to a specific time node, wherein each thinning process data is from first thinning data to Nth thinning data; generating a first refined secret key according to the first refined data based on a preset specific Hash algorithm, wherein the specific Hash algorithm is an HMAC algorithm; generating a process data abstract according to the first refining data and the first refining secret key, and recording the process data abstract as a first process abstract; and acquiring process data summaries generated according to the second refined data to the Nth refined data in sequence based on the HMAC algorithm, and storing each process data summary to a preset big data storage module.
Optionally, in the food material supply management system based on big data, a plurality of food material arrangement points are arranged in the food material management warehouse, and each food material arrangement point is provided with a food material arrangement manipulator; the food material transportation robot comprises a robot main body, a motion monitoring transducer array, a position adjusting driving mechanism and a position adjusting transducer array; the top end of the robot main body is used for bearing food materials, and the motion monitoring transducer array is installed on the robot main body and used for acquiring motion information of the robot main body; the position adjusting driving mechanism is arranged on the robot main body, is also connected with the position adjusting transducer array and drives the position adjusting transducer array to move; the system further comprises:
the motion monitoring module is used for acquiring current actual linear distance data between the robot main body and the food material arranging manipulator based on the robot main body and the motion monitoring transducer array;
the food material transportation module is used for judging a main control unit based on food materials preset by the food material transportation robot and judging whether the current actual linear distance data is smaller than or equal to a preset settleable linear distance or not;
the linear distance module is used for adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained if the current actual linear distance data is judged to be not less than or equal to the preset placeable linear distance;
and the actual adjustment module is used for generating placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, controlling the robot main body to move to a position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
Optionally, the system further comprises:
the actual straight line module is used for acquiring the image data of the current position of the position adjusting transducer array based on the image acquisition device and sending the image data of the current position to the food material judging main control unit if the current actual straight line distance data is judged to be not less than or equal to the preset mountable straight line distance;
a position adjustment module, configured to acquire, based on the position adjustment transducer array, a current detectable trigger range detected by the position adjustment transducer array at a current position in the current position image data;
a module, configured to determine, based on the current detectable trigger range, whether a food material borne by the robot main body and a farthest trigger range edge of the food material placement manipulator are included in the current detectable trigger range;
the farthest triggering module is used for generating a position driving adjustment instruction if the farthest triggering range edge of the food material loaded on the robot main body and the food material arranging manipulator is judged not to be included in the current detectable triggering range;
and the drive adjusting module is used for controlling the position adjusting drive mechanism to adjust the position adjusting transducer array to obtain the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator through the food material judging main control unit based on the position drive adjusting instruction.
Specifically, the system further comprises:
the acquisition device module is used for acquiring image data of an obstructing object which obstructs the robot main body from moving to a triggerable range of the food material arranging manipulator in an obstructing area formed by taking the actual distance to be adjusted as a core based on the image acquisition device;
the passing path module is used for generating a plurality of pieces of passable path data according to the image data of the obstructing object, the actual distance to be adjusted and the current actual linear distance data;
the setting target module is used for screening out the shortest route from the multiple passable route data and setting the data corresponding to the route as the settable target route data;
the food material judgment main control unit is used for controlling the robot main body to move to a position matched with the placeable target path data, generating placement process data and storing the placement process data based on big data;
the main body movement module is used for acquiring surrounding obstacle information in the placeable target path data in real time based on the movement monitoring transducer and the image acquisition device in the robot main body movement process;
the monitoring and energy conversion module is used for comparing the surrounding obstacle information respectively acquired by the motion monitoring energy converter and the image acquisition device and generating actual obstacle information;
and the obstacle clearing machine module is used for sending the actual obstacle information to the obstacle clearing robot and controlling the obstacle clearing robot to clear the obstacles contained in the actual obstacle information.
Specifically, the computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the big data-based food material supply management method when executing the computer program.
Specifically, a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the above-described big data based food material supply management method.
The invention has the following technical effects:
according to the food material supply management method and system based on the big data, the food material transportation robot and the image acquisition device are sequentially arranged in sequence, the food material transportation robot is arranged in a food material management warehouse, a plurality of food material arrangement points are arranged in the food material management warehouse, and each food material arrangement point is provided with a food material arrangement mechanical arm; the image acquisition device is arranged in the food material management warehouse and is used for detecting and acquiring image information in the food material management warehouse; the food material transportation robot comprises a robot main body, a motion monitoring transducer array, a position adjusting driving mechanism and a position adjusting transducer array; the top end of the robot main body is used for bearing food materials, and the motion monitoring transducer array is installed on the robot main body and used for acquiring motion information of the robot main body; the position adjusting driving mechanism is arranged on the robot main body, is also connected with the position adjusting transducer array and drives the position adjusting transducer array to move; the method comprises the following steps: acquiring current actual linear distance data between the robot main body and the food material placing manipulator based on the robot main body and the motion monitoring transducer array; judging whether the current actual linear distance data is smaller than or equal to a preset settleable linear distance or not by a main control unit based on food preset by the food transport robot; if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained; generating placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, controlling the robot main body to move to a position matched with the placeable target path data by the food material judgment main control unit, and then firstly judging whether the current actual linear distance data is less than or equal to a preset placeable linear distance by the food material judgment main control unit preset based on the food material transportation robot, and when the judgment is negative, the food material cannot be effectively placed and managed by the food material placement manipulator, so that the position adjustment transducer array is adjusted based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material carried on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained, and then generating the placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, through the food material judgment main control unit controls the robot main body to move to the position where the target path data can be arranged to be matched, fine adjustment of the position is achieved, food material arrangement mechanical arms can conduct food material management and arrangement according to the current position, food material arrangement and management processing efficiency is improved, and in addition, data can be supported for follow-up big data analysis through arrangement process data based on big data storage.
Drawings
Fig. 1 is a schematic flow chart of a big data-based food material supply management method according to an embodiment;
fig. 2 is a block diagram of a big data based food supply management system according to an embodiment;
FIG. 3 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, a big data-based food material supply management method is provided, and is characterized in that the method is based on a food material transportation robot, the food material transportation robot is arranged in a food material management warehouse, a plurality of food material arrangement points are arranged in the food material management warehouse, and each food material arrangement point is provided with a food material arrangement mechanical arm; the food material transportation robot comprises a robot main body, a motion monitoring transducer array, a position adjusting driving mechanism and a position adjusting transducer array; the top end of the robot main body is used for bearing food materials, and the motion monitoring transducer array is installed on the robot main body and used for acquiring motion information of the robot main body; the position adjusting driving mechanism is arranged on the robot main body, is also connected with the position adjusting transducer array and drives the position adjusting transducer array to move.
Specifically, the method comprises the following steps:
step S100: acquiring current actual linear distance data between the robot main body and the food material placing manipulator based on the robot main body and the motion monitoring transducer array;
specifically, in this embodiment, the motion monitoring transducer array is adopted to monitor and acquire the motion distance of the robot body in the motion process and the related distance data in real time. In this step, the current actual linear distance data between the robot main body and the food material placing manipulator is obtained.
Further, the motion monitoring transducer array described herein is an array of multiple transducers arranged in a pattern, and may be understood to be similar to an antenna array. Each of the motion monitoring transducers is referred to as an element or array element.
In this step, the number of the motion monitoring transducer arrays is multiple, so that it is ensured that the current actual linear distance data is accurately and efficiently acquired in real time.
Step S200: judging whether the current actual linear distance data is smaller than or equal to a preset settleable linear distance or not by a main control unit based on food preset by the food transport robot;
specifically, in this embodiment, when the food material transportation robot is located within the placeable linear distance, it indicates that the food material transportation robot is located within the controllable range of the food material placement manipulator, and at this time, the food material transportation robot may be disassembled and transported by the food material placement manipulator.
And when the food material conveying robot is not in the placeable linear distance, the situation that the food material conveying robot is not in the controllable range of the food material placing mechanical arm at the moment is shown, and the goods can not be disassembled and transferred to the food material conveying robot through the food material placing mechanical arm.
Therefore, in the step, whether the current actual linear distance data is smaller than or equal to the preset placeable linear distance is judged, whether the current actual linear distance data is within the controllable range of the food material placement manipulator is judged, and whether the obtained goods can be detached through the food material transportation robot is judged.
Step S300: if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained;
specifically, in this embodiment, if it is determined that the current actual linear distance data is not less than or equal to the preset placeable linear distance, it indicates that the current actual linear distance data is not within the controllable range of the food material placement manipulator, and it may be that an obstacle exists in a specific position away from the food material placement manipulator, so that the food material transportation robot cannot reach the effective controllable range of the food material placement manipulator, and therefore, the cargo can not be disassembled and transported to the food material transportation robot through the food material placement manipulator, and therefore, it is obviously necessary to adjust the position of the robot main body.
Therefore, by the step, the position adjustment transducer is adjusted to obtain the actual distance to be adjusted between the food material loaded on the robot body and the farthest triggering range edge of the food material placement manipulator.
Because of can make to eat material and settle the manipulator and carry out goods dismantlement and transportation to eating material transport robot in order to realize more accurately after the adjustment, consequently, through the adjustment position adjustment transducer array to can acquireing, the material of eating born in the robot main part with eat the material and settle treating the adjustment actual distance between the farthest triggering range edge of manipulator, also directly acquire the area of transporting eat the material with eat the material and settle the distance between the farthest triggering range edge of manipulator, also promptly treat the adjustment actual distance.
Step S400: generating placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, controlling the robot main body to move to a position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
Specifically, in this embodiment, the mountable target path data is generated based on the actual distance to be adjusted and the current actual linear distance data, so that the path to be moved, that is, the mountable target path data, is efficiently and accurately acquired.
And then, controlling the robot main body to move to a position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
In the process, the arrangement process data are generated, so that the data generated in the food material transportation process can be effectively utilized and stored, and meanwhile, the process data can be conveniently analyzed and processed based on a big data technology in the follow-up process, and then the feedback data can be generated more accurately.
In one embodiment, the food material management warehouse is also provided with an image acquisition device, and the image acquisition device is arranged in the food material management warehouse and is used for detecting and acquiring image information in the food material management warehouse;
step S300: if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained; the method specifically comprises the following steps:
step S310: if the current actual linear distance data is judged to be not less than or equal to the preset mountable linear distance, acquiring current position image data of the position adjustment transducer array based on the image acquisition device, and sending the current position image data to the food material judgment main control unit;
step S320: acquiring a current detectable trigger range detected by the position adjusting transducer array at a current position in the current position image data based on the position adjusting transducer array;
step S330: judging whether the current detectable trigger range contains food materials borne by the robot main body and the farthest trigger range edge of the food material arranging manipulator or not;
step S340: if the current detectable trigger range does not contain the food materials loaded on the robot main body and the farthest trigger range edge of the food material placing manipulator, generating a position driving adjustment instruction;
step S350: based on the position driving adjustment instruction, the food material judgment main control unit controls the position adjustment driving mechanism to adjust the position adjustment transducer array to obtain the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator.
Specifically, in this embodiment, by setting the image acquisition device, and sending the image data of the current position of the position adjustment transducer array acquired by the image acquisition device to the food material judgment main control unit, the food material judgment main control unit can acquire the position information according to the image data of the current position.
In addition, the position adjustment transducer array is used for acquiring a current detectable trigger range detected by the position adjustment transducer array at the current position in the current position image data, and considering the possible obstruction of the position where food materials are placed, the position adjustment transducer array is not necessarily capable of detecting food materials, so that by acquiring the current detectable trigger range and based on the current detectable trigger range, whether the farthest trigger range edge of the food materials loaded on the robot main body and the food material placement manipulator is included in the current detectable trigger range is judged, and when the farthest trigger range edge of the food materials loaded on the robot main body and the food material placement manipulator is not included in the current detectable trigger range is judged, a position driving adjustment instruction is generated, and simultaneously, the messenger is based on position drive adjustment instruction, through it judges the main control unit control to eat material position adjustment actuating mechanism adjustment position adjustment transducer array to acquireing the material of eating that bears in the robot main part with eat the material and settle treating between the farthest triggering range edge of manipulator and adjust the actual distance, and then based on image acquisition device and position adjustment transducer array, realized through the adjustment, guaranteed position adjustment actuating mechanism adjustment position adjustment transducer array to acquireing the material of eating that bears in the robot main part with eat and settle treating between the farthest triggering range edge of manipulator and adjust the actual distance, consequently, further realized follow-up accurate adjustment, promote goods and transport efficiency.
In one embodiment, step S400: generating settleable target path data based on the actual distance to be adjusted and the current actual linear distance data, judging a position where the robot main body moves and matches the settleable target path data through the food material, controlling the robot main body to move by the main control unit, generating settleable process data, and storing the settleable process data based on big data, wherein the settleable target path data specifically comprises the following steps:
step S410: based on the image acquisition device, in an obstruction area formed by taking the actual distance to be adjusted as a core, obstructing object image data which obstructs the robot main body to move to a triggerable range of the food material arranging manipulator;
step S420: generating a plurality of passable path data according to the image data of the obstructing object, the actual distance to be adjusted and the current actual linear distance data;
step S430: screening out the shortest route from the multiple passable route data, and setting the data corresponding to the route as placeable target route data;
step S440: and controlling the robot main body to move to the position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
Specifically, in this embodiment, the blocking area formed by taking the actual distance to be adjusted as a core refers to an area formed by uniformly diverging the actual distance to be adjusted by a specific distance outward, which is the blocking area.
Through obtaining in the hindering district, hinder the robot main part move to but eat the hindrance object image data of material arrangement manipulator's triggerable within range, can realize according to hinder object image data wait to adjust actual distance with present actual straight-line distance data generate many passable route data, passable route data is after avoiding each barrier, reach and to make the robot main part move to but eat the triggerable within range of material arrangement manipulator.
Then, in order to ensure resource saving and achieve the purpose that the shortest path reaches the destination, a path with the shortest path is screened out from the plurality of pieces of passable path data, data corresponding to the path is set as placeable target path data, the food material judgment main control unit controls the robot main body to move to a position matched with the placeable target path data, placement process data are generated, and the placement process data are stored based on big data.
In one embodiment, a barrier removing robot is further disposed in the food material management warehouse, and step S440: through the edible material judges that the main control unit control the robot main part moves as to can settle target path data assorted position, and generate and settle process data, will settle process data is based on big data storage, specifically includes:
step S441: acquiring surrounding obstacle information in the placeable target path data in real time based on the motion monitoring transducer and the image acquisition device during the motion of the robot body;
step S442: comparing the peripheral obstacle information respectively acquired by the motion monitoring transducer and the image acquisition device, and generating actual obstacle information;
step S443: and sending the actual obstacle information to an obstacle removing robot, and controlling the obstacle removing robot to remove the obstacles contained in the actual obstacle information.
Specifically, in this embodiment, in order to ensure that the road condition is updated in real time according to the change of the obstacle during the movement, the robot body acquires the information of the peripheral obstacle in the placeable target path data in real time based on the movement monitoring transducer and the image acquisition device during the movement, and in order to accurately determine the obstacle, the information of the peripheral obstacle acquired by the movement monitoring transducer and the image acquisition device is compared with each other, and actual obstacle information is generated, so that the actual obstacle information can be sent to the obstacle clearing robot, and the obstacle clearing robot is controlled to clear the obstacle included in the actual obstacle information, thereby accurately determining and removing the obstacle.
In one embodiment, the storing the installation process data based on big data specifically includes:
step S451: splitting the installation process data into a plurality of thinning process data according to a specific time node, wherein each thinning process data is from first thinning data to Nth thinning data;
step S452: generating a first refined secret key according to the first refined data based on a preset specific Hash algorithm, wherein the specific Hash algorithm is an HMAC algorithm;
step S453: generating a process data abstract according to the first refining data and the first refining secret key, and recording the process data abstract as a first process abstract;
step S454: and acquiring process data summaries generated according to the second refined data to the Nth refined data in sequence based on the HMAC algorithm, and storing each process data summary to a preset big data storage module.
Specifically, in the present embodiment, an HMAC algorithm is adopted, the HMAC algorithm takes a message X and a key Y as inputs, and generates a message digest with a fixed length as an output, the algorithm introduces the key, and the security of the algorithm does not completely depend on the Hash algorithm used. Therefore, based on the algorithm, the process data abstracts generated according to the second refined data to the Nth refined data are obtained, the process data abstracts are stored in a preset big data storage module, and meanwhile, the data are refined and stored through the splitting processing of the data.
The big data storage module is a big data-based storage module selected and set by a person skilled in the art according to actual needs, and efficient and rapid storage based on big data is further realized.
In summary, the food material transportation robot and the image acquisition device are sequentially arranged on the basis of the food material transportation robot, the food material transportation robot is arranged in a food material management warehouse, a plurality of food material arrangement points are arranged in the food material management warehouse, and each food material arrangement point is provided with a food material arrangement mechanical arm; the image acquisition device is arranged in the food material management warehouse and is used for detecting and acquiring image information in the food material management warehouse; the food material transportation robot comprises a robot main body, a motion monitoring transducer array, a position adjusting driving mechanism and a position adjusting transducer array; the top end of the robot main body is used for bearing food materials, and the motion monitoring transducer array is installed on the robot main body and used for acquiring motion information of the robot main body; the position adjusting driving mechanism is arranged on the robot main body, is also connected with the position adjusting transducer array and drives the position adjusting transducer array to move; the method comprises the following steps: acquiring current actual linear distance data between the robot main body and the food material placing manipulator based on the robot main body and the motion monitoring transducer array; judging whether the current actual linear distance data is smaller than or equal to a preset settleable linear distance or not by a main control unit based on food preset by the food transport robot; if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained; generating placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, controlling the robot main body to move to a position matched with the placeable target path data by the food material judgment main control unit, and then firstly judging whether the current actual linear distance data is less than or equal to a preset placeable linear distance by the food material judgment main control unit preset based on the food material transportation robot, and when the judgment is negative, the food material cannot be effectively placed and managed by the food material placement manipulator, so that the position adjustment transducer array is adjusted based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material carried on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained, and then generating the placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, through the food material judgment main control unit controls the robot main body to move to the position where the target path data can be arranged to be matched, fine adjustment of the position is achieved, food material arrangement mechanical arms can conduct food material management and arrangement according to the current position, food material arrangement and management processing efficiency is improved, and in addition, data can be supported for follow-up big data analysis through arrangement process data based on big data storage.
In one embodiment, as shown in fig. 2, a big data based food material supply management system, the system comprising: the food material transportation robot is arranged in a food material management warehouse, a plurality of food material arrangement points are arranged in the food material management warehouse, and each food material arrangement point is provided with a food material arrangement mechanical arm; the food material transportation robot comprises a robot main body, a motion monitoring transducer array, a position adjusting driving mechanism and a position adjusting transducer array; the top end of the robot main body is used for bearing food materials, and the motion monitoring transducer array is installed on the robot main body and used for acquiring motion information of the robot main body; the position adjusting driving mechanism is arranged on the robot main body, is also connected with the position adjusting transducer array and drives the position adjusting transducer array to move; the system further comprises:
the motion monitoring module is used for acquiring current actual linear distance data between the robot main body and the food material arranging manipulator based on the robot main body and the motion monitoring transducer array;
the food material transportation module is used for judging a main control unit based on food materials preset by the food material transportation robot and judging whether the current actual linear distance data is smaller than or equal to a preset settleable linear distance or not;
the linear distance module is used for adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained if the current actual linear distance data is judged to be not less than or equal to the preset placeable linear distance;
and the actual adjustment module is used for generating placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, controlling the robot main body to move to a position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
In one embodiment, the system further comprises:
the actual straight line module is used for acquiring the image data of the current position of the position adjusting transducer array based on the image acquisition device and sending the image data of the current position to the food material judging main control unit if the current actual straight line distance data is judged to be not less than or equal to the preset mountable straight line distance;
a position adjustment module, configured to acquire, based on the position adjustment transducer array, a current detectable trigger range detected by the position adjustment transducer array at a current position in the current position image data;
a module, configured to determine, based on the current detectable trigger range, whether a food material borne by the robot main body and a farthest trigger range edge of the food material placement manipulator are included in the current detectable trigger range;
the farthest triggering module is used for generating a position driving adjustment instruction if the farthest triggering range edge of the food material loaded on the robot main body and the food material arranging manipulator is judged not to be included in the current detectable triggering range;
and the drive adjusting module is used for controlling the position adjusting drive mechanism to adjust the position adjusting transducer array to obtain the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator through the food material judging main control unit based on the position drive adjusting instruction.
In one embodiment, the system further comprises:
the acquisition device module is used for acquiring image data of an obstructing object which obstructs the robot main body from moving to a triggerable range of the food material arranging manipulator in an obstructing area formed by taking the actual distance to be adjusted as a core based on the image acquisition device;
the passing path module is used for generating a plurality of pieces of passable path data according to the image data of the obstructing object, the actual distance to be adjusted and the current actual linear distance data;
the setting target module is used for screening out the shortest route from the multiple passable route data and setting the data corresponding to the route as the settable target route data;
the food material judgment main control unit is used for controlling the robot main body to move to a position matched with the placeable target path data, generating placement process data and storing the placement process data based on big data;
the main body movement module is used for acquiring surrounding obstacle information in the placeable target path data in real time based on the movement monitoring transducer and the image acquisition device in the robot main body movement process;
the monitoring and energy conversion module is used for comparing the surrounding obstacle information respectively acquired by the motion monitoring energy converter and the image acquisition device and generating actual obstacle information;
and the obstacle clearing machine module is used for sending the actual obstacle information to the obstacle clearing robot and controlling the obstacle clearing robot to clear the obstacles contained in the actual obstacle information.
In one embodiment, the monitoring transducer module is further configured to: splitting the installation process data into a plurality of thinning process data according to a specific time node, wherein each thinning process data is from first thinning data to Nth thinning data; generating a first refined secret key according to the first refined data based on a preset specific Hash algorithm, wherein the specific Hash algorithm is an HMAC algorithm; generating a process data abstract according to the first refining data and the first refining secret key, and recording the process data abstract as a first process abstract; and acquiring process data summaries generated according to the second refined data to the Nth refined data in sequence based on the HMAC algorithm, and storing each process data summary to a preset big data storage module.
In one embodiment, as shown in fig. 3, a computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above-mentioned big-data-based food material supply management method when executing the computer program.
In one embodiment, the processor is configured to perform: acquiring current actual linear distance data between the robot main body and the food material placing manipulator based on the robot main body and the motion monitoring transducer array; judging whether the current actual linear distance data is smaller than or equal to a preset settleable linear distance or not by a main control unit based on food preset by the food transport robot; if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained; generating placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, controlling the robot main body to move to a position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data; if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained; the method specifically comprises the following steps: if the current actual linear distance data is judged to be not less than or equal to the preset mountable linear distance, acquiring current position image data of the position adjustment transducer array based on the image acquisition device, and sending the current position image data to the food material judgment main control unit; acquiring a current detectable trigger range detected by the position adjusting transducer array at a current position in the current position image data based on the position adjusting transducer array; judging whether the current detectable trigger range contains food materials borne by the robot main body and the farthest trigger range edge of the food material arranging manipulator or not; if the current detectable trigger range does not contain the food materials loaded on the robot main body and the farthest trigger range edge of the food material placing manipulator, generating a position driving adjustment instruction; based on the position driving adjustment instruction, the food material judgment main control unit controls the position adjustment driving mechanism to adjust the position adjustment transducer array to obtain the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator.
In one embodiment, a computer readable storage medium has a computer program stored thereon, and the computer program when executed by a processor implements the steps of the above-mentioned big data based food material supply management method.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A food material supply management method based on big data is characterized in that the method is based on a food material transportation robot, the food material transportation robot is arranged in a food material management warehouse, a plurality of food material arrangement points are arranged in the food material management warehouse, and each food material arrangement point is provided with a food material arrangement mechanical arm; the food material transportation robot comprises a robot main body, a motion monitoring transducer array, a position adjusting driving mechanism and a position adjusting transducer array; the top end of the robot main body is used for bearing food materials, and the motion monitoring transducer array is installed on the robot main body and used for acquiring motion information of the robot main body; the position adjusting driving mechanism is arranged on the robot main body, is also connected with the position adjusting transducer array and drives the position adjusting transducer array to move; the method comprises the following steps:
acquiring current actual linear distance data between the robot main body and the food material placing manipulator based on the robot main body and the motion monitoring transducer array; judging whether the current actual linear distance data is smaller than or equal to a preset settleable linear distance or not by a main control unit based on food preset by the food transport robot; if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained; generating placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, controlling the robot main body to move to a position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
2. The big-data based food material supply management method according to claim 1, wherein an image acquisition device is further installed in the food material management warehouse, and is used for detecting and acquiring image information in the food material management warehouse;
if the current actual linear distance data is judged not to be less than or equal to the preset placeable linear distance, adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained; the method specifically comprises the following steps: if the current actual linear distance data is judged to be not less than or equal to the preset mountable linear distance, acquiring current position image data of the position adjustment transducer array based on the image acquisition device, and sending the current position image data to the food material judgment main control unit; acquiring a current detectable trigger range detected by the position adjusting transducer array at a current position in the current position image data based on the position adjusting transducer array; judging whether the current detectable trigger range contains food materials borne by the robot main body and the farthest trigger range edge of the food material arranging manipulator or not; if the current detectable trigger range does not contain the food materials loaded on the robot main body and the farthest trigger range edge of the food material placing manipulator, generating a position driving adjustment instruction; based on the position driving adjustment instruction, the food material judgment main control unit controls the position adjustment driving mechanism to adjust the position adjustment transducer array to obtain the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator.
3. The big-data based food material supply management method according to claim 2, wherein the step S400: generating settleable target path data based on the actual distance to be adjusted and the current actual linear distance data, judging a position where the robot main body moves and matches the settleable target path data through the food material, controlling the robot main body to move by the main control unit, generating settleable process data, and storing the settleable process data based on big data, wherein the settleable target path data specifically comprises the following steps:
based on the image acquisition device, in an obstruction area formed by taking the actual distance to be adjusted as a core, obstructing object image data which obstructs the robot main body to move to a triggerable range of the food material arranging manipulator; generating a plurality of passable path data according to the image data of the obstructing object, the actual distance to be adjusted and the current actual linear distance data; screening out the shortest route from the multiple passable route data, and setting the data corresponding to the route as placeable target route data; and controlling the robot main body to move to the position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
4. The food material supply management method based on big data as claimed in claim 3, wherein a barrier removing robot is further arranged in the food material management warehouse, the food material judgment main control unit controls the robot main body to move to a position matched with the placeable target path data, placement process data is generated, and the placement process data is stored based on big data, specifically comprising:
acquiring surrounding obstacle information in the placeable target path data in real time based on the motion monitoring transducer and the image acquisition device during the motion of the robot body; comparing the peripheral obstacle information respectively acquired by the motion monitoring transducer and the image acquisition device, and generating actual obstacle information; and sending the actual obstacle information to an obstacle removing robot, and controlling the obstacle removing robot to remove the obstacles contained in the actual obstacle information.
5. The big data based food material supply management method according to any one of claims 1-4, wherein the storing the placement process data based on big data specifically comprises:
splitting the installation process data into a plurality of thinning process data according to a specific time node, wherein each thinning process data is from first thinning data to Nth thinning data; generating a first refined secret key according to the first refined data based on a preset specific Hash algorithm, wherein the specific Hash algorithm is an HMAC algorithm; generating a process data abstract according to the first refining data and the first refining secret key, and recording the process data abstract as a first process abstract; and acquiring process data summaries generated according to the second refined data to the Nth refined data in sequence based on the HMAC algorithm, and storing each process data summary to a preset big data storage module.
6. A big data based food material supply management system, characterized in that the system comprises: the food material transportation robot is arranged in a food material management warehouse, a plurality of food material arrangement points are arranged in the food material management warehouse, and each food material arrangement point is provided with a food material arrangement mechanical arm; the food material transportation robot comprises a robot main body, a motion monitoring transducer array, a position adjusting driving mechanism and a position adjusting transducer array; the top end of the robot main body is used for bearing food materials, and the motion monitoring transducer array is installed on the robot main body and used for acquiring motion information of the robot main body; the position adjusting driving mechanism is arranged on the robot main body, is also connected with the position adjusting transducer array and drives the position adjusting transducer array to move; the system further comprises:
the motion monitoring module is used for acquiring current actual linear distance data between the robot main body and the food material arranging manipulator based on the robot main body and the motion monitoring transducer array;
the food material transportation module is used for judging a main control unit based on food materials preset by the food material transportation robot and judging whether the current actual linear distance data is smaller than or equal to a preset settleable linear distance or not;
the linear distance module is used for adjusting the position adjustment transducer array based on the position adjustment driving mechanism until the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator is obtained if the current actual linear distance data is judged to be not less than or equal to the preset placeable linear distance;
and the actual adjustment module is used for generating placeable target path data based on the actual distance to be adjusted and the current actual linear distance data, controlling the robot main body to move to a position matched with the placeable target path data through the food material judgment main control unit, generating placement process data, and storing the placement process data based on big data.
7. The big data-based food material supply management system according to claim 6, further comprising:
the actual straight line module is used for acquiring the image data of the current position of the position adjusting transducer array based on the image acquisition device and sending the image data of the current position to the food material judging main control unit if the current actual straight line distance data is judged to be not less than or equal to the preset mountable straight line distance;
a position adjustment module, configured to acquire, based on the position adjustment transducer array, a current detectable trigger range detected by the position adjustment transducer array at a current position in the current position image data;
a module, configured to determine, based on the current detectable trigger range, whether a food material borne by the robot main body and a farthest trigger range edge of the food material placement manipulator are included in the current detectable trigger range;
the farthest triggering module is used for generating a position driving adjustment instruction if the farthest triggering range edge of the food material loaded on the robot main body and the food material arranging manipulator is judged not to be included in the current detectable triggering range;
and the drive adjusting module is used for controlling the position adjusting drive mechanism to adjust the position adjusting transducer array to obtain the actual distance to be adjusted between the food material loaded on the robot main body and the farthest triggering range edge of the food material placement manipulator through the food material judging main control unit based on the position drive adjusting instruction.
8. The big data-based food material supply management system according to claim 6, further comprising:
the acquisition device module is used for acquiring image data of an obstructing object which obstructs the robot main body from moving to a triggerable range of the food material arranging manipulator in an obstructing area formed by taking the actual distance to be adjusted as a core based on the image acquisition device;
the passing path module is used for generating a plurality of pieces of passable path data according to the image data of the obstructing object, the actual distance to be adjusted and the current actual linear distance data;
the setting target module is used for screening out the shortest route from the multiple passable route data and setting the data corresponding to the route as the settable target route data;
the food material judgment main control unit is used for controlling the robot main body to move to a position matched with the placeable target path data, generating placement process data and storing the placement process data based on big data;
the main body movement module is used for acquiring surrounding obstacle information in the placeable target path data in real time based on the movement monitoring transducer and the image acquisition device in the robot main body movement process;
the monitoring and energy conversion module is used for comparing the surrounding obstacle information respectively acquired by the motion monitoring energy converter and the image acquisition device and generating actual obstacle information;
and the obstacle clearing machine module is used for sending the actual obstacle information to the obstacle clearing robot and controlling the obstacle clearing robot to clear the obstacles contained in the actual obstacle information.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 5 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 5.
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