CN109732615A - Cooking robot and its cooking control method, device, storage medium and server - Google Patents
Cooking robot and its cooking control method, device, storage medium and server Download PDFInfo
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- CN109732615A CN109732615A CN201811535239.3A CN201811535239A CN109732615A CN 109732615 A CN109732615 A CN 109732615A CN 201811535239 A CN201811535239 A CN 201811535239A CN 109732615 A CN109732615 A CN 109732615A
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Abstract
The present invention provides a kind of cooking robot and its cooking control method, device, storage medium and server, which comprises obtains the corresponding cooking status detection model of every kind of food materials in the food materials that dish to be cooked is included；The corresponding cooking status detection model of every kind of food materials is carried out obtained from model training respectively based on the cooking status data of the every kind of food materials collected in advance during the cooking process；When carrying out the culinary art of the dish, it is based on the corresponding cooking status detection model of every kind of food materials, the robot is controlled and every kind of food materials of the dish is individually cooked；Every kind of food materials in the food materials for being included by the dish are cooked to default cooking status, are controlled the food materials that the robot is included to the dish and are carried out mixing culinary art.Scheme provided by the invention can control cooking robot and individually cook every kind of food materials of dish to optimum state, and then Hybrid Heating, meets requirement of the user to every kind of food materials.
Description
Technical field
The present invention relates to robot field more particularly to a kind of cooking robot and its cooking control method, device, storages
Medium and server.
Background technique
Currently, robot application rests on mechanical labour aspect, lack the application of poly-talented labour.Robot dish-cooking
Difficult point be to identify whether dish is delicious, edible, be not complete enough only by the simple technology such as image recognition
Kind, it is therefore desirable to propose the scheme of more optimized robot dish-cooking.
Summary of the invention
It is a primary object of the present invention to overcome the defect of the above-mentioned prior art, a kind of cooking robot and its culinary art are provided
Control method, device, storage medium and server only pass through image recognition to solve robot dish-cooking in the prior art
The problem incomplete etc. simple technology.
One aspect of the present invention provides a kind of cooking control method of cooking robot, comprising: obtains dish to be cooked
The corresponding cooking status detection model of every kind of food materials in the food materials for being included；The corresponding cooking status of every kind of food materials detects mould
Type is carried out obtained from model training respectively based on the cooking status data of the every kind of food materials collected in advance during the cooking process；
When carrying out the culinary art of the dish, it is based on the corresponding cooking status detection model of every kind of food materials, controls the robot
Every kind of food materials of the dish are individually cooked；Every kind of food materials in the food materials for being included by the dish are cooked to pre-
If after cooking status, controlling the food materials that the robot is included to the dish and carrying out mixing culinary art.
Optionally, the robot has analog vision nervous system, simulation olfactory neural system and/or simulation sense of taste mind
Through system；Based on the corresponding cooking status detection model of every kind of food materials, every kind of food materials of the dish are individually cooked
It prepares food, comprising: adopted respectively by the analog vision nervous system, simulation olfactory neural system and/or simulation gustatory nerve system
Collect color information, odiferous information and/or the mouthfeel information of every kind of food materials；Every kind of food materials based on acquisition are corresponding to be cooked
State-detection of preparing food model carries out mould to the color information of every kind of food materials of acquisition, odiferous information and/or mouthfeel information respectively
Type matching detection；According to the matching result for carrying out the Model Matching, the cooking process of every kind of food materials is adjusted, so that described
Every kind of food materials reach default cooking status.
Optionally, according to the matching result for carrying out the Model Matching, the cooking process of every kind of food materials, packet are adjusted
Include: when any food materials Model Matching matching result be the food materials color information, odiferous information and/or mouthfeel information with
When the corresponding default culinary art Model Matching of the food materials, the culinary art of the food materials is completed.
Optionally, it is based on the corresponding cooking status detection model of every kind of food materials, controls the robot to the dish
Every kind of food materials of meat and fish dishes are individually cooked, further includes: edible oil information used in the culinary art for carrying out the dish are obtained, to obtain
Take default edible oil heating duration of the every kind of food materials of the dish when being cooked using the edible oil；To described every
When kind food materials are individually cooked, after the used edible oil heating default edible oil heating duration, cooked described in control
The corresponding food materials of robot addition of preparing food are cooked.
Optionally, cooking status data, comprising: dryout temperature, temperature of smoldering, decomposition product, each period
At least one of C/Hratio.
Another aspect of the present invention provides a kind of culinary art control device of cooking robot, comprising: model acquiring unit is used
The corresponding cooking status detection model of every kind of food materials in the food materials that acquisition dish to be cooked is included；Every kind of food materials are corresponding
The cooking status detection model be based on the every kind of food materials collected in advance cooking status data during the cooking process respectively into
Obtained from row model training；Independent control unit, for being based on every kind of food materials pair when carrying out the culinary art of the dish
The cooking status detection model answered controls the cooking robot and individually cooks to every kind of food materials of the dish；And
Mixed control unit, every kind of food materials in the food materials for being included by the dish are cooked to default cooking status, are controlled
It makes the food materials that the cooking robot is included to the dish and carries out mixing culinary art.
Optionally, the cooking robot has analog vision nervous system, simulation olfactory neural system and/or simulation taste
Feel nervous system；The independent control unit, comprising: acquisition subelement, for passing through the analog vision nervous system, simulation
Olfactory neural system and/or simulation gustatory nerve system acquire respectively the color informations of every kind of food materials, odiferous information and/or
Mouthfeel information；Detection sub-unit, for the corresponding cooking status detection model of every kind of food materials based on acquisition, respectively to adopting
Color information, odiferous information and/or the mouthfeel information of every kind of food materials of collection carry out Model Matching detection；Regulator unit,
For adjusting the cooking process of every kind of food materials according to the matching result for carrying out the Model Matching, so that every kind of food
Material reaches default cooking status.
Optionally, the adjusting unit adjusts every kind of food materials according to the matching result for carrying out the Model Matching
Cooking process, comprising: when the matching result of the Model Matching of any food materials be the color informations of the food materials, odiferous information and/
Or when corresponding with the food materials default culinary art Model Matching of mouthfeel information, complete the culinary art of the food materials.
Optionally, the independent control unit, further includes: subelement is obtained, for obtaining the culinary art for carrying out the dish
Used edible oil information, to obtain default food of the every kind of food materials of the dish when being cooked using the edible oil
Duration is heated with oil；Subelement is controlled, for when individually cooking to every kind of food materials, used edible oil to be added
After the heat default edible oil heating duration, controls the corresponding food materials of the cooking robot addition and cooked.
Optionally, cooking status data, comprising: dryout temperature, temperature of smoldering, decomposition product, each period
At least one of C/Hratio.
Another aspect of the invention provides a kind of storage medium, is stored thereon with computer program, and described program is processed
The step of device realizes aforementioned any the method when executing.
Further aspect of the present invention provides a kind of cooking robot, including processor, memory and is stored in memory
On the computer program that can run on a processor, the processor realizes aforementioned any the method when executing described program
Step.
Further aspect of the present invention provides a kind of cooking robot, including aforementioned any culinary art control device.
Further aspect of the present invention provides a kind of server, including processor, memory and storage on a memory may be used
The computer program run on a processor, the processor realize the step of aforementioned any the method when executing described program
Suddenly.
Further aspect of the present invention provides a kind of server, the culinary art control including aforementioned any cooking robot
Device.
According to the technique and scheme of the present invention, cooking robot can be controlled individually to cook every kind of food materials of dish to best
State, then Hybrid Heating, a kind of dish of user demand are that various food materials units combine, and need to only be directed to each food materials
Unit is cooked to best, is finally mixed with certain hybrid mode to optimum state；And the present invention can be based on preparatory
The corresponding cooking status detection model of every kind of food materials established, and using analog vision, smell and/or gustatory nerve system to every
Whether kind food materials, which reach optimized cooking state, is detected, and reaches nearest cooking status so as to control every kind of food materials.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present invention, constitutes a part of the invention, this hair
Bright illustrative embodiments and their description are used to explain the present invention, and are not constituted improper limitations of the present invention.In the accompanying drawings:
Fig. 1 is the method schematic diagram of an embodiment of the cooking control method of cooking robot provided by the invention；
Fig. 2 is the function distribution map of the culinary art control of cooking robot according to an embodiment of the present invention；
Fig. 3 is the workflow schematic diagram of cooking robot according to an embodiment of the present invention；
Fig. 4 is according to an embodiment of the present invention based on the corresponding default culinary art model of every kind of food materials, to the dish
Every kind of food materials the step of individually being cooked flow diagram；
Fig. 5 is the structural schematic diagram of an embodiment of the culinary art control device of cooking robot provided by the invention；
Fig. 6 is a kind of structural schematic diagram of embodiment of independent control unit according to an embodiment of the present invention.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with the specific embodiment of the invention and
Technical solution of the present invention is clearly and completely described in corresponding attached drawing.Obviously, described embodiment is only the present invention one
Section Example, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not doing
Every other embodiment obtained under the premise of creative work out, shall fall within the protection scope of the present invention.
It should be noted that description and claims of this specification and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " includes " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, for example, the process, method, system, product or equipment for containing a series of steps or units are not necessarily limited to
Step or unit those of is clearly listed, but may include be not clearly listed or for these process, methods, product
Or other step or units that equipment is intrinsic.
The present invention provides a kind of cooking control method of cooking robot.The present invention can be implemented in server side, or
Implement at cooking robot side (for example, in robot controller).
Fig. 2 is the function distribution map of the culinary art control of cooking robot according to an embodiment of the present invention.As shown in Fig. 2, A01
For data source, A02 is the cloud computing platform (abbreviation cloud platform) of server maintenance, and A03 is robot controller, and A10 is simulation
Visual system, A11 are simulation olfactory neural system, and A12 is simulation gustatory nerve system, and A09 is cooking robot entity,
B01 is instruction execution unit.
By chemical analysis (such as carbohydrate content, large biological molecule content, metallic ore content of material, the water of food materials on the market
Content, flue gas ratio when heating, each component content of flue gas etc.), characteristic (decomposition product content and reaction speed under such as aerobic and high temperature
Rate, decomposition product content and reaction rate under few oxygen and high temperature, flue gas ratio when heating), and physics composition (such as impurity, it is extraneous
Water), the data summarizations such as characteristic (such as humidity, temperature, hardness), database is written, by data cleansing, extracts effective number
According to.It is data source A01 by this numerical nomenclature.
A whole set of cloud computing platform cloud platform A02 that service management is carried out to data source A01, tool are safeguarded and run to server
Standby function: Data Matching, detection data reasonability, record new data, datagraphic show, the relationships of data and model parameter
Maintenance etc..
Fig. 1 is the method schematic diagram of an embodiment of the cooking control method of cooking robot provided by the invention.
As shown in Figure 1, according to one embodiment of present invention, the robot cooking control method includes at least step
S110, step S120 and step S130.
Step S110 obtains the corresponding default culinary art model of every kind of food materials in the food materials that dish to be cooked is included.
The corresponding default cooking status detection model of every kind of food materials is based on the every kind of food materials collected in advance in cooking process
In cooking status data carry out obtained from model training respectively.The cooking status data are for example including dryouting temperature, emit
At least one of smoke temperature degree, decomposition product, C/Hratio of each period.
It is illustrated below with reference to model training process of the example to cooking status detection model.For example, Kung Pao chicken, packet
Include food materials: chicken breast meat, shelled peanut, pimiento, Bulbus Allii Fistulosi, ginger.The task of 5 model trainings of correspondence establishment, with " detection therein
Chicken breast meat is heated to optimum state " for model training.The number of all associated valid datas of chicken breast meat is obtained from A01 data source
According to collection, (each data is all one group and similar dryouies temperature, temperature of smoldering, decomposition product, C/Hratio of each period etc.
, the data set of such data composition " detection chicken breast meat is heated to best condition " model parameter training), pass through related algorithm
Processing, obtains the model parameter of " detection chicken breast meat is heated to best condition ", and the cooking status for establishing detection chicken breast meat detects mould
Type, and give parameter to A02 processing.It obtains 10,000 data at random from A01 again, this cooking status detection model is surveyed
Examination, does not pass through, and continues training pattern parameter.By later, giving cooking status detection model to cloud computing platform A02 processing.
A02 is responsible for cooking status detection model accessing A03 controller.The step of can specifically being executed with reference to cloud computing platform in Fig. 3.
Step S120 is based on the corresponding default culinary art model of every kind of food materials when carrying out the culinary art of the dish, right
Every kind of food materials of the dish are individually cooked.
Every kind of food materials are individually heated to optimum state, then Hybrid Heating.Being equivalent to every kind of food materials all is an element
(water is no exception), each element, which can allow, drinks material mixing composition food materials unit, and a kind of dish of user demand is various food materials
What unit combined, it need to only be cooked for each food materials unit to best, finally be mixed.
There is analog vision nervous system (for example, electronic eyes based on simulated nervous system), simulation to smell for the robot
Feel nervous system (for example, electronic nose based on simulated nervous system) and/or simulation gustatory nerve system (for example, based on simulation
The electronic tongues of nervous system).
Fig. 4 is according to an embodiment of the present invention based on the corresponding default culinary art model of every kind of food materials, to the dish
Every kind of food materials the step of individually being cooked flow diagram.As shown in figure 4, in a specific embodiment, step
S120 includes step S121, step S122 and step S123.
Step S121 passes through the analog vision nervous system, simulation olfactory neural system and/or simulation gustatory nerve system
System acquires color information, odiferous information and/or the mouthfeel information of every kind of food materials respectively.
Specifically, the color information for acquiring every kind of food materials of the dish in real time by analog vision nervous system, passes through
The simulation olfactory neural system acquires the odiferous information of every kind of food materials of the dish in real time, and/or passes through the simulation taste
Feel that nervous system acquires the mouthfeel information of every kind of food materials of the dish in real time.
Step S122, the corresponding cooking status detection model of every kind of food materials based on acquisition, respectively to the institute of acquisition
Color information, odiferous information and/or the mouthfeel information for stating every kind of food materials carry out Model Matching detection.
That is, by the color information of every kind of food materials of acquisition, odiferous information and/or the corresponding culinary art of mouthfeel information input
State-detection model is matched, to obtain matching result.
Step S123 adjusts the cooking process of every kind of food materials according to the matching result for carrying out the Model Matching, with
Every kind of food materials are made to reach default cooking status.
Specifically, can temperature to the cooking tools (for example, pot) where food materials and/or pressure be adjusted.When any
The matching result of the Model Matching of food materials is color information, odiferous information and/or the mouthfeel information and the food materials pair of the food materials
When the default culinary art Model Matching answered, the culinary art of the food materials is completed.
Continue to use the example of " chicken breast meat " of " Kung Pao chicken " above-mentioned below to illustrate.It can be combined with Fig. 3 simultaneously,
In, Fig. 3 is the workflow schematic diagram of cooking robot according to an embodiment of the present invention.Robot has vision, smell, the sense of taste
Three kinds of simulated nervous systems pass through the Nerve Testings such as real-time Transmission color, smell, mouthfeel signal to controller A03, this nerve inspection
The digital signal that signal is really a kind of complexity is surveyed, for convenience of description process, description are as follows: color, smell, mouthfeel.Controller A03
Nerve Testing signal is transferred to cloud platform A02 by Internet of Things communication mode.Cloud platform A02 prepares corresponding cooking status inspection
Model is surveyed, and by carrying out value needed for resolving to model to Nerve Testing signal, carries out Model Matching and detects to obtain detection knot
Fruit, cloud platform A02 continue to testing result carry out matching detection (matching criteria derive from experimental summary data source A01, most preferably
State: color is best, taste is best, smell is best), see whether meet optimum state.If color, mouthfeel, three Xiang Doufu of taste
It closes, cloud platform A02 sends the instruction execution unit B01 stopping that control instruction controls robot to controller A03, controller A03
The culinary art of " chicken breast meat ".Conversely, sending corresponding regulating command (such as corresponding temperature, pressure control instruction) to controller
A03, controller A03 control instruction execution unit B01 make adjustment, until meeting optimum state.
Equally, other food materials of " Kung Pao chicken " complete corresponding Model Matching detection, are according to similar above-mentioned step
It is no to meet optimum state.Wherein, the meals with wine such as pimiento, ginger, soy sauce, vinegar, oil, salt material can add during every kind of food heating
Add, with no restrictions.
Further, it obtains and carries out edible oil information used in the culinary art of the dish, to obtain the every of the dish
Default edible oil of the kind food materials when being cooked using the edible oil heats duration；It is individually carried out to every kind of food materials
When culinary art, after the used edible oil heating default edible oil heating duration, corresponding food materials is added and are cooked.Its
In, the default edible oil of the every kind of food materials when being cooked using the edible oil heats duration, i.e. every kind of food materials make
When being heated to heating needed for presetting cooking temp (for example, optimized cooking temperature) accordingly when being cooked with the edible oil
It is long；The default edible oil heating duration of the every kind of food materials when being cooked using the edible oil is passed through to the food
The chemical component in heating process is carried out with oil to detect (for example, temperature variation data, the oil smoke composition to edible oil are examined
Survey) and/or using the edible oil cuisine experiment acquisition is individually carried out to every kind of food materials.
Specifically, it is detected by temperature variation data, the oil smoke composition to edible oil, obtaining edible oil can mix most
The good time, (edible oil reached the time span of optimum temperature from heating, Temperature-time coordinate diagram can be drawn by experiment, most
In the case that good temperature determines, this temperature corresponding time only need to be found, edible oil can be obtained from heating and reach optimum temperature
Time span.)；By can mix Best Times based on this and individually tested to all kinds of food materials, obtain in heating process
Other physical feature, chemical feature, and combine preset algorithm simulate regression equation, to provide food materials tripping in cooking tools
The step of default edible oil before (for example, pot) heats duration, can specifically refer to test block in Fig. 3.For example, in the market
Every kind of edible oil carries out analysis of components, extract heating speed, boiling point, temperature of smoldering, dryout temperature, centre smolders the number such as temperature
According to calculate common food materials optimized cooking temperature collection TempList1.Cooking robot is boiled by monitoring oil, emits oil smoke, emits
The data access data source A01 such as the equal stages are dryouied after cigarette, and record temperature, time.Cloud platform A02 is according to food materials optimized cooking temperature
The rate curve (Temperature-time) of degree and robot heating edible oil, fitting optimal time convergent point, (robot heats certain
The rate curve of kind edible oil can draw temperature-time curve figure by experiment, true in the optimized cooking temperature of certain food materials
In the case where calmly, this temperature corresponding time only need to be found on curve, and the edible oil can be obtained and be heated to food materials correspondence
Optimized cooking temperature duration), show that Various Edible and different food materials are suitble to best by many experiments discrete data
It is (i.e. described default edible that (this is one several groups recurrence numbers, is the regression data of a large amount of optimum datas) edible oil heats duration
Oil heating duration) BestTemp, and access data source A01.Controller A03 is obtained by network communication from cloud platform A02 corresponding
Data, corresponding control is made to robot, for example, heating edible oil to optimum temperature, food materials are then added.
Optionally, image library can also be established by machine vision training image.By testing as much as possible obtain often
Kind food materials correspond to edible, inedible, the best edible tri stage image of every kind of edible oil, by many experiments or simulation
Image library is established in experiment, carries out image recognition by big data processing, artificial intelligence image procossing etc., trains a set of identification most
The algorithm of good edible image calls the algorithm to identify the image data acquired in real time, judges whether to reach optimal in culinary art
Edible opportunity, so that control cooking robot stops culinary art when reaching most preferably edible opportunity.
Optionally, in addition to image procossing can also carry out chemical analysis to the gas molecule in cooking environments, to reach pair
The final confirmation of the best ready state of the dish of culinary art.By many experiments, every kind of food materials are corresponded into every kind of edible oil
And the aerochemistry composition during the meal with wine material mixed culinary art of equal proportion being equipped with is detected, and is handled by preset algorithm
Optimal aerochemistry component ratio out.When cooking robot detects that the various aerochemistry component ratios in air reach pre-
If triggering the algorithm of best edible image when critical value, starts to acquire image, gas detection is then turned on after images match.That is,
By actually detected aerochemistry constituent data, itself and preset optimal gas chemical analysis are compared.This process can be by taking
Business device executes.In conjunction with image recognition result, server returns to controller and is sent completely cooking instruction.
Step S130, every kind of food materials in the food materials for being included by the dish are cooked cook state to default shape after, it is right
The food materials that the dish is included carry out mixing culinary art.
It is all mixing food materials regardless of soup, custard, Sichuan cuisine, Guangdong dishes because the essence of every kind of dish is all the mixing of food materials unit
Unit forms, and every kind of food materials in the food materials for being included by dish are cooked to after default cooking status (optimum state), to institute
It states the food materials that dish is included and carries out mixing culinary art.
The present invention specifically can carry out centralized services to data Layer and apparatus control layer using cloud computing platform, when each
Cooking status model foundation is got up, this cloud platform is all accessed.When controller receives the letter that machine human's nervous system transmits
Number, all transfer to this cloud platform to handle, and make corresponding control to controller, to control the operation behavior of robot.This hair
The specific implementation process of bright each section can refer to Fig. 3.
Fig. 5 is the structural schematic diagram of an embodiment of the culinary art control device of cooking robot provided by the invention.Such as Fig. 5
Shown, the culinary art control device 100 of the cooking robot includes: model acquiring unit 110, independent control unit 120 and mixes
Close control unit 130.
Model acquiring unit 110 is for obtaining the corresponding culinary art shape of every kind of food materials in the food materials that dish to be cooked is included
State detection model.Wherein, the corresponding cooking status detection model of every kind of food materials is existed based on the every kind of food materials collected in advance
Cooking status data in cooking process carry out obtained from model training respectively.The cooking status data are for example including dryouting
At least one of temperature, temperature of smoldering, decomposition product, C/Hratio of each period.
It is illustrated below with reference to model training process of the example to cooking status detection model.It can be combined with figure simultaneously
3, wherein Fig. 3 is the workflow schematic diagram of cooking robot according to an embodiment of the present invention.For example, Kung Pao chicken, including food
Material: chicken breast meat, shelled peanut, pimiento, Bulbus Allii Fistulosi, ginger.The task of 5 model trainings of correspondence establishment, with " detection chicken breast therein
Meat is heated to optimum state " for model training.The data set of all associated valid datas of chicken breast meat is obtained from A01 data source
(each data be all one group it is similar dryout temperature, temperature of smoldering, decomposition product, C/Hratio of each period etc., this
The data set of data composition " detection chicken breast meat is heated to best condition " model parameter training of sample), it is handled by related algorithm,
The model parameter for obtaining " detection chicken breast meat is heated to best condition ", establishes the cooking status detection model C01 of detection chicken breast meat,
And give parameter to A02 processing.It obtains 10,000 data at random from A01 again, this cooking status detection model is tested,
Do not pass through, continues training pattern parameter.By later, giving cooking status detection model to cloud computing platform A02 processing.A02
It is responsible for cooking status detection model accessing A03 controller.The step of can specifically being executed with reference to cloud computing platform in Fig. 3.
Independent control unit 120 is used to be based on the corresponding culinary art of every kind of food materials when carrying out the culinary art of the dish
State-detection model controls the cooking robot and individually cooks to every kind of food materials of the dish.
Every kind of food materials are individually heated to optimum state, then Hybrid Heating.Being equivalent to every kind of food materials all is an element
(water is no exception), each element, which can allow, drinks material mixing composition food materials unit, and a kind of dish of user demand is various food materials
What unit combined, it need to only be cooked for each food materials unit to best, finally be mixed.
In a specific embodiment, the robot has analog vision nervous system (for example, being based on analog neuron
The electronic eyes of system), simulation olfactory neural system (for example, electronic nose based on simulated nervous system) and/or simulation the sense of taste mind
Through system (for example, electronic tongues based on simulated nervous system).
Fig. 6 is a kind of structural schematic diagram of embodiment of independent control unit according to an embodiment of the present invention.Such as Fig. 6 institute
Show, in a specific embodiment, independent control unit 120 includes acquisition subelement 121, detection sub-unit 122 and adjusts
Subelement 123.
Subelement 121 is acquired to be used for through the analog vision nervous system, simulation olfactory neural system and/or simulation taste
Feel that nervous system acquires color information, odiferous information and/or the mouthfeel information of every kind of food materials respectively；That is, passing through simulation view
Feel that nervous system acquires the color information of every kind of food materials of the dish in real time, is adopted in real time by the simulation olfactory neural system
Collect the odiferous information of every kind of food materials of the dish, and/or the dish is acquired by the simulation gustatory nerve system in real time
Every kind of food materials mouthfeel information.
Detection sub-unit 122 is used for the corresponding cooking status detection model of every kind of food materials based on acquisition, right respectively
Color information, odiferous information and/or the mouthfeel information of every kind of food materials of acquisition carry out Model Matching detection；That is, will acquisition
The color informations of every kind of food materials, odiferous information and/or the corresponding cooking status detection model of mouthfeel information input carry out
Matching, to obtain matching result.
Regulator unit 123 is used to adjust cooking for every kind of food materials according to the matching result for carrying out the Model Matching
It prepares food process, so that every kind of food materials reach default cooking status.
Specifically, can temperature to the cooking tools (for example, pot) where food materials and/or pressure be adjusted.When any
The matching result of the Model Matching of food materials is color information, odiferous information and/or the mouthfeel information and the food materials pair of the food materials
When the default culinary art Model Matching answered, the culinary art of the food materials is completed.
Continue to use the example of " chicken breast meat " of " Kung Pao chicken " above-mentioned below to illustrate.It can be combined with Fig. 3 simultaneously,
In, Fig. 3 is the workflow schematic diagram of cooking robot according to an embodiment of the present invention.Robot has vision, smell, the sense of taste
Three kinds of simulated nervous systems pass through the Nerve Testings such as real-time Transmission color, smell, mouthfeel signal to controller A03, this nerve inspection
The digital signal that signal is really a kind of complexity is surveyed, for convenience of description process, description are as follows: color, smell, mouthfeel.Controller A03
Nerve Testing signal is transferred to cloud platform A02 by Internet of Things communication mode.Cloud platform A02 prepares corresponding cooking status inspection
Model is surveyed, and by carrying out value needed for resolving to model to Nerve Testing signal, carries out Model Matching and detects to obtain detection knot
Fruit, cloud platform A02 continue to testing result carry out matching detection (matching criteria derive from experimental summary data source A01, most preferably
State: color is best, taste is best, smell is best), see whether meet optimum state.If color, mouthfeel, three Xiang Doufu of taste
It closes, cloud platform A02 sends the instruction execution unit B01 stopping that control instruction controls robot to controller A03, controller A03
The culinary art of " chicken breast meat ".Conversely, sending corresponding regulating command (such as corresponding temperature, pressure control instruction) to controller
A03, controller A03 control instruction execution unit B01 make adjustment, until meeting optimum state.
Equally, other food materials of " Kung Pao chicken " complete corresponding Model Matching detection, are according to similar above-mentioned step
It is no to meet optimum state.Wherein, the meals with wine such as pimiento, ginger, soy sauce, vinegar, oil, salt material can add during every kind of food heating
Add, with no restrictions.
Further, the independent control unit 120 further includes obtaining subelement and control subelement (not shown).
Subelement is obtained, edible oil information used in the culinary art of the dish is carried out for obtaining, to obtain the dish
Default edible oil of the every kind of food materials of meat and fish dishes when being cooked using the edible oil heats duration；Subelement is controlled, is used for
When individually being cooked to every kind of food materials, after the used edible oil heating default edible oil heating duration, control
The corresponding food materials of the cooking robot addition are made to be cooked.
Wherein, the default edible oil of the every kind of food materials when being cooked using the edible oil heats duration, i.e., often
Kind food materials are heated to presetting cooking temp (for example, optimized cooking temperature) institute accordingly when being cooked using the edible oil
The heating duration needed；The default edible oil heating duration of the every kind of food materials when being cooked using the edible oil is logical
Cross to the edible oil carry out in heating process chemical component detection (for example, to the temperature variation data of edible oil, oil smoke at
Part detected) and/or using the edible oil cuisine experiment acquisition is individually carried out to every kind of food materials.
Specifically, it is detected by temperature variation data, the oil smoke composition to edible oil, obtaining edible oil can mix most
The good time, (edible oil reached the time span of optimum temperature from heating, Temperature-time coordinate diagram can be drawn by experiment, most
In the case that good temperature determines, this temperature corresponding time only need to be found, edible oil can be obtained from heating and reach optimum temperature
Time span.)；By can mix Best Times based on this and individually tested to all kinds of food materials, obtain in heating process
Other physical feature, chemical feature, and combine preset algorithm simulate regression equation, to provide food materials tripping in cooking tools
The step of default edible oil before (for example, pot) heats duration, can specifically refer to test block in Fig. 3.For example, in the market
Every kind of edible oil carries out analysis of components, extract heating speed, boiling point, temperature of smoldering, dryout temperature, centre smolders the number such as temperature
According to calculate common food materials optimized cooking temperature collection TempList1.Cooking robot is boiled by monitoring oil, emits oil smoke, emits
The data access data source A01 such as the equal stages are dryouied after cigarette, and record temperature, time.Cloud platform A02 is according to food materials optimized cooking temperature
The rate curve (Temperature-time) of degree and robot heating edible oil, fitting optimal time convergent point, (robot heats certain
The rate curve of kind edible oil can draw temperature-time curve figure by experiment, true in the optimized cooking temperature of certain food materials
In the case where calmly, this temperature corresponding time only need to be found on curve, and the edible oil can be obtained and be heated to food materials correspondence
Optimized cooking temperature duration), show that Various Edible and different food materials are suitble to best by many experiments discrete data
It is (i.e. described default edible that (this is one several groups recurrence numbers, is the regression data of a large amount of optimum datas) edible oil heats duration
Oil heating duration) BestTemp, and access data source A01.Controller A03 is obtained by network communication from cloud platform A02 corresponding
Data, corresponding control is made to robot, for example, heating edible oil to optimum temperature, food materials are then added.
Optionally, image library can also be established by machine vision training image.By testing as much as possible obtain often
Kind food materials correspond to edible, inedible, the best edible tri stage image of every kind of edible oil, by many experiments or simulation
Image library is established in experiment, carries out image recognition by big data processing, artificial intelligence image procossing etc., trains a set of identification most
The algorithm of good edible image calls the algorithm to identify the image data acquired in real time, judges whether to reach optimal in culinary art
Edible opportunity, so that control cooking robot stops culinary art when reaching most preferably edible opportunity.
Optionally, in addition to image procossing can also carry out chemical analysis to the gas molecule in cooking environments, to reach pair
The final confirmation of the best ready state of the dish of culinary art.By many experiments, every kind of food materials are corresponded into every kind of edible oil
And the aerochemistry composition during the meal with wine material mixed culinary art of equal proportion being equipped with is detected, and is handled by preset algorithm
Optimal aerochemistry component ratio out.When cooking robot detects that the various aerochemistry component ratios in air reach pre-
If triggering the algorithm of best edible image when critical value, starts to acquire image, gas detection is then turned on after images match.That is,
By actually detected aerochemistry constituent data, itself and preset optimal gas chemical analysis are compared.This process can be by taking
Business device executes.In conjunction with image recognition result, server returns to controller and is sent completely cooking instruction.
Every kind of food materials that mixed control unit 130 is used in the food materials for being included by the dish are cooked to default culinary art
After state, controls the food materials that the cooking robot is included to the dish and carry out mixing culinary art.
Specifically, because the mixing that the essence of every kind of dish is all food materials unit is all regardless of soup, custard, Sichuan cuisine, Guangdong dishes
Mixing food materials unit forms, and every kind of food materials in the food materials for being included by dish are cooked to default cooking status (optimum state)
Afterwards, the food materials for being included to the dish carry out mixing culinary art.
The present invention also provides a kind of storage mediums for the cooking control method for corresponding to the cooking robot, store thereon
The step of having computer program, aforementioned any the method is realized when described program is executed by processor.
The present invention also provides a kind of cooking robots for the cooking control method for corresponding to the cooking robot, including place
It manages device, memory and stores the computer program that can be run on a processor on a memory, described in the processor execution
The step of aforementioned any the method is realized when program.
It is including preceding the present invention also provides a kind of cooking robot for the culinary art control device for corresponding to the cooking robot
State the culinary art control device of any cooking robot.
The present invention also provides a kind of servers for the cooking control method for corresponding to the cooking robot, including processing
The computer program that device, memory and storage can be run on a processor on a memory, the processor execute the journey
The step of aforementioned any the method is realized when sequence.
The present invention also provides a kind of servers for the culinary art control device for corresponding to the cooking robot, including aforementioned
The culinary art control device of cooking robot described in one.
Accordingly, scheme provided by the invention can control cooking robot and individually cook every kind of food materials of dish to most
Good state, then Hybrid Heating, a kind of dish of user demand are that various food materials units combine, and need to only be directed to each food
Material unit is cooked to best, is finally mixed with certain hybrid mode to optimum state；And the present invention can be based on pre-
The corresponding cooking status detection model of the every kind of food materials first established, and utilize analog vision, smell and/or gustatory nerve system pair
Whether every kind of food materials, which reach optimized cooking state, is detected, and reaches nearest cooking status so as to control every kind of food materials.
Function described herein can be implemented in hardware, the software executed by processor, firmware or any combination thereof.
If implemented in the software executed by processor, computer can be stored in using function as one or more instructions or codes
It is transmitted on readable media or via computer-readable media.Other examples and embodiment are wanted in the present invention and appended right
It asks in the scope and spirit of book.For example, due to the property of software, function described above can be used by processor,
Hardware, firmware, hardwired or the software implementation for appointing the combination of whichever to execute in these.In addition, each functional unit can integrate
In one processing unit, it is also possible to each unit to physically exist alone, can also be integrated in two or more units
In one unit.
In several embodiments provided herein, it should be understood that disclosed technology contents can pass through others
Mode is realized.Wherein, the apparatus embodiments described above are merely exemplary, such as the division of the unit, Ke Yiwei
A kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or components can combine or
Person is desirably integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING or communication link of unit or module
It connects, can be electrical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, and fill as control
The component set may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
On unit.It can some or all of the units may be selected to achieve the purpose of the solution of this embodiment according to the actual needs.
If the integrated unit is realized in the form of SFU software functional unit and sells or use as independent product
When, it can store in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially
The all or part of the part that contributes to existing technology or the technical solution can be in the form of software products in other words
It embodies, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can for personal computer, server or network equipment etc.) execute each embodiment the method for the present invention whole or
Part steps.And storage medium above-mentioned includes: that USB flash disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic or disk etc. be various to can store program code
Medium.
The above description is only an embodiment of the present invention, is not intended to restrict the invention, for those skilled in the art
For member, the invention may be variously modified and varied.All within the spirits and principles of the present invention, it is made it is any modification,
Equivalent replacement, improvement etc., should be included within scope of the presently claimed invention.
Claims (15)
1. a kind of cooking control method of cooking robot characterized by comprising
Obtain the corresponding cooking status detection model of every kind of food materials in the food materials that dish to be cooked is included；Every kind of food materials are corresponding
The cooking status detection model be based on the every kind of food materials collected in advance during the cooking process cooking status data difference
It carries out obtained from model training；
When carrying out the culinary art of the dish, it is based on the corresponding cooking status detection model of every kind of food materials, controls the machine
Device people individually cooks every kind of food materials of the dish；
Every kind of food materials in the food materials for being included by the dish are cooked to default cooking status, and the robot pair is controlled
The food materials that the dish is included carry out mixing culinary art.
2. the method according to claim 1, wherein the robot has analog vision nervous system, simulation
Olfactory neural system and/or simulation gustatory nerve system；
Based on the corresponding cooking status detection model of every kind of food materials, every kind of food materials of the dish are individually cooked,
Include:
Institute is acquired respectively by the analog vision nervous system, simulation olfactory neural system and/or simulation gustatory nerve system
State the color information, odiferous information and/or mouthfeel information of every kind of food materials；
The corresponding cooking status detection model of every kind of food materials based on acquisition, respectively to the color of every kind of food materials of acquisition
Multimedia message, odiferous information and/or mouthfeel information carry out Model Matching detection；
According to the matching result for carrying out the Model Matching, the cooking process of every kind of food materials is adjusted, so that every kind of food
Material reaches default cooking status.
3. according to the method described in claim 2, it is characterized in that, being adjusted according to the matching result for carrying out the Model Matching
The cooking process of every kind of food materials, comprising:
When color information, odiferous information and/or the mouthfeel information that the matching result of the Model Matching of any food materials is the food materials
When default culinary art Model Matching corresponding with the food materials, the culinary art of the food materials is completed.
4. the method according to claim 1, wherein detecting mould based on the corresponding cooking status of every kind of food materials
Type controls the robot and individually cooks to every kind of food materials of the dish, further includes:
It obtains and carries out edible oil information used in the culinary art of the dish, using institute to obtain every kind of food materials of the dish
State default edible oil heating duration when edible oil is cooked；
When individually cooking to every kind of food materials, the used edible oil heating default edible oil is heated into duration
Afterwards, the corresponding food materials of the cooking robot addition are controlled to be cooked.
5. the method according to claim 1, wherein the cooking status data, comprising: dryout temperature, smolder
At least one of temperature, decomposition product, C/Hratio of each period.
6. a kind of culinary art control device of cooking robot characterized by comprising
Model acquiring unit, for obtaining the corresponding cooking status detection of every kind of food materials in the food materials that dish to be cooked is included
Model；The corresponding cooking status detection model of every kind of food materials be based on the every kind of food materials collected in advance during the cooking process
Cooking status data carry out obtained from model training respectively；
Independent control unit, for being examined based on the corresponding cooking status of every kind of food materials when carrying out the culinary art of the dish
Model is surveyed, the cooking robot is controlled and every kind of food materials of the dish is individually cooked；And
Mixed control unit, every kind of food materials in the food materials for being included by the dish are cooked to default cooking status
Afterwards, the food materials that the cooking robot is included to the dish are controlled and carry out mixing culinary art.
7. device according to claim 6, which is characterized in that the cooking robot have analog vision nervous system,
Simulate olfactory neural system and/or simulation gustatory nerve system；
The independent control unit, comprising:
Subelement is acquired, for passing through the analog vision nervous system, simulation olfactory neural system and/or simulation gustatory nerve
System acquires color information, odiferous information and/or the mouthfeel information of every kind of food materials respectively；
Detection sub-unit, for the corresponding cooking status detection model of every kind of food materials based on acquisition, respectively to acquisition
Color information, odiferous information and/or the mouthfeel information of every kind of food materials carry out Model Matching detection；
Regulator unit, for adjusting the cooking process of every kind of food materials according to the matching result for carrying out the Model Matching,
So that every kind of food materials reach default cooking status.
8. device according to claim 7, which is characterized in that the adjusting unit, according to the progress Model Matching
Matching result adjusts the cooking process of every kind of food materials, comprising:
When color information, odiferous information and/or the mouthfeel information that the matching result of the Model Matching of any food materials is the food materials
When default culinary art Model Matching corresponding with the food materials, the culinary art of the food materials is completed.
9. device according to claim 6, which is characterized in that the independent control unit, further includes:
Subelement is obtained, edible oil information used in the culinary art of the dish is carried out for obtaining, to obtain the dish
Default edible oil of the every kind of food materials when being cooked using the edible oil heats duration；
Subelement is controlled, for used edible oil being heated described pre- when individually cooking to every kind of food materials
If after edible oil heats duration, controlling the corresponding food materials of the cooking robot addition and being cooked.
10. device according to claim 6, which is characterized in that the cooking status data, comprising: dryout temperature, smolder
At least one of temperature, decomposition product, C/Hratio of each period.
11. a kind of storage medium, which is characterized in that it is stored thereon with computer program, it is real when described program is executed by processor
The step of existing claim 1-5 any the method.
12. a kind of cooking robot, which is characterized in that can handled on a memory including processor, memory and storage
The computer program run on device, the processor realize the step of claim 1-5 any the method when executing described program
Suddenly.
13. a kind of cooking robot, which is characterized in that including the culinary art control device as described in claim 6-10 is any.
14. a kind of server, which is characterized in that on a memory can be on a processor including processor, memory and storage
The step of computer program of operation, the processor realizes claim 1-5 any the method when executing described program.
15. a kind of server, which is characterized in that the culinary art control including the cooking robot as described in claim 6-10 is any
Device.
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