CN114670196A - Automatic planning integrated service system based on artificial intelligence - Google Patents
Automatic planning integrated service system based on artificial intelligence Download PDFInfo
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- CN114670196A CN114670196A CN202210315845.4A CN202210315845A CN114670196A CN 114670196 A CN114670196 A CN 114670196A CN 202210315845 A CN202210315845 A CN 202210315845A CN 114670196 A CN114670196 A CN 114670196A
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- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 13
- 230000005484 gravity Effects 0.000 claims abstract description 51
- 210000001747 pupil Anatomy 0.000 claims abstract description 46
- 235000013305 food Nutrition 0.000 claims abstract description 38
- 238000007405 data analysis Methods 0.000 claims abstract description 37
- 238000012544 monitoring process Methods 0.000 claims abstract description 35
- 230000008859 change Effects 0.000 claims abstract description 15
- 235000013361 beverage Nutrition 0.000 claims description 21
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- 238000010191 image analysis Methods 0.000 claims description 12
- 230000008054 signal transmission Effects 0.000 claims description 12
- 238000000034 method Methods 0.000 claims description 11
- 235000012054 meals Nutrition 0.000 claims description 9
- 230000004044 response Effects 0.000 claims description 9
- 230000001815 facial effect Effects 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 230000006698 induction Effects 0.000 claims description 6
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- 230000035622 drinking Effects 0.000 claims description 2
- 230000010354 integration Effects 0.000 claims 5
- 230000005540 biological transmission Effects 0.000 description 9
- 230000005611 electricity Effects 0.000 description 6
- 210000000887 face Anatomy 0.000 description 4
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1679—Programme controls characterised by the tasks executed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
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Abstract
The invention discloses an automatic planning integrated service system based on artificial intelligence, which comprises a sensing module, a state monitoring module, a data analysis module and a speed control module, wherein the sensing module is used for sensing and detecting the start-stop time of a worker for serving dishes, and the gravity of the desktop, the state monitoring module is used for monitoring the face state of the worker during the dish transferring, the state monitoring module is connected with the sensing module through a network, the data analysis module is used for analyzing the pupil change of the staff when the staff transmits the dish, and calculates the concentration value of the staff when the dish is delivered through the pupil change value, the data analysis module is electrically connected with the state monitoring module, the invention discloses a food delivery system, which comprises a food delivery robot, a speed control module, a data analysis module, a speed control module, a food delivery speed control module and a food delivery speed control module.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an automatic planning integrated service system based on artificial intelligence.
Background
With the rapid development of scientific and discipline technology, the catering robot is moving into the lives of people, after the advantages and the disadvantages of the existing catering robot are analyzed, a novel catering robot is designed, and the intelligent monitoring function is utilized to solve the problems encountered in the meal delivery process.
The appearance of the catering robot replaces some traditional catering industries, a part of labor cost is saved, but some problems are exposed, when people manually serve dishes, people can avoid obstacles on a route in advance through sensory awareness to avoid the loss of the dishes, compared with the catering robot, the catering robot can start an automatic obstacle avoiding function according to a path planned in advance, when the obstacles are met, the automatic obstacle avoiding function can be started, meanwhile, the dishes can be lost due to the inertia effect, the satisfaction degree of consumers to the dishes is reduced to a certain degree, and therefore, the automatic planning integrated service system based on artificial intelligence is necessary for controlling the dish transmission speed according to the state.
Disclosure of Invention
The invention aims to provide an automatic planning integrated service system based on artificial intelligence to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the utility model provides an automatic planning integrated service system based on artificial intelligence, including the response module, state monitoring module, data analysis module, the fast module of accuse, the response module is used for responding to the change that detects desktop weight and take place, and signal transmission who will accord with dish weight standard gives food and beverage robot, state monitoring module is used for monitoring staff face state when biography dish, state monitoring module and response module internet access, data analysis module is arranged in passing dish staff's pupil in the image and carries out the analysis, so that calculate the concentration value of staff when passing dish, data analysis module is connected with the state monitoring module electricity, the fast module of accuse is used for controlling the speed when food and beverage robot send meal, in order to guarantee the integrity of dish, the fast module of accuse is connected with data analysis module electricity.
According to the technical scheme, the response module includes gravity detection module, gravity analysis module and signal transmission unit, gravity detection module is used for detecting the change that the desktop end gravity of placing the dish takes place, gravity analysis module is used for judging whether the gravity change accords with the weight interval standard of dish, gravity analysis module is connected with gravity detection module electricity, signal transmission unit is used for passing through the network with the signal that accords with the interval standard of dish weight and transmitting for catering robot, so that the supplementary dynamic camera function of opening, signal transmission unit is connected with gravity analysis module electricity, the change of gravity on the response module mainly used monitoring desktop, and the function of transmission signal.
According to the technical scheme, the state monitoring module comprises a signal receiving unit, a dynamic camera module and a gravity sensing module, the signal receiving unit is used for receiving network signals and starting the camera function of the catering robot, the dynamic camera module is used for collecting facial images of workers in dish transferring, the dynamic camera function is electrically connected with the signal receiving function, the gravity sensing unit is used for sensing the weight of the workers when the workers place dishes on the catering robot and feeding back data to the state monitoring module, the gravity sensing unit is electrically connected with the dynamic camera module, the dynamic camera module comprises a face tracking unit and a data storage unit, the face tracking unit is used for shooting the faces of the workers in dish transferring, the data storage unit is used for storing the obtained face images, the data storage unit is electrically connected with the face tracking unit, and the state monitoring module is mainly used for the catering robot to shoot the faces of the workers in dish transferring, and the image is stored and then transmitted to the data analysis module.
According to the technical scheme, the data analysis module comprises an image analysis module and a logic judgment unit, the image analysis module is used for analyzing facial images of the workers who pass dishes, the logic judgment unit is used for judging states of the workers when the dishes are passed, the logic judgment unit is electrically connected with the image analysis module, the image analysis module comprises a time reading unit and a pupil tracking unit, the time reading module is used for reading starting and ending time L of the workers who send the dishes in the images, the pupil tracking unit is used for tracking pupil changes of the workers when the dishes are passed, and the data analysis module is mainly used for analyzing the pupil changes of the workers when the dishes are passed in the images and recording the starting and ending time L of the dishes.
According to the technical scheme, the speed control module comprises a data matching unit and a speed execution unit, the data matching unit is used for matching a proper dish transmission speed according to the state of a worker, the speed execution unit is used for executing the dish transmission speed of the catering robot, the speed execution unit is electrically connected with the data matching unit, the speed control module is mainly used for adjusting the dish sending speed of the catering robot according to the result analyzed by data, the data matching unit comprises a client feedback unit and an intelligent optimization unit, the client feedback unit is used for analyzing the feedback of a client, the intelligent optimization unit is used for finely adjusting the current speed, and the intelligent optimization unit is electrically connected with the client feedback unit.
According to the technical scheme, the operation method of the automatic planning integrated service system based on the artificial intelligence comprises the following steps:
step S1: after the consumer successfully places an order, the staff prepares dishes according to the menu and puts the dishes on a desktop with an induction module;
step S2: when a worker starts dishes from the desktop end with the sensing module, the desktop end with the sensing module sends a signal to the catering robot, and the catering robot starts to work;
step S3: a state monitoring module of the catering robot end is started to shoot and collect the face state of the current worker;
step S4: the catering robot can analyze the collected data, judge the state of the staff when the dish is delivered by analyzing the pupils of the staff delivering the dish and taking the time of the staff when the dish is delivered as a basis, adjust the speed of the catering robot when the dish is delivered according to the state of the staff when the dish is delivered, and deliver the dish to the room of a consumer;
step S5: the catering robot further optimizes the speed according to the feedback of the client, and finally sends dishes to a room of a consumer.
According to the above technical solution, the step S3 further includes the following steps:
step S31: after the catering robot receives the signal sent by the induction module, the dynamic camera module starts to work to track the face of a worker who passes dishes;
step S32: when a worker places dishes on the catering robot, the gravity sensing module is triggered, the gravity sensing module can judge whether the dishes accord with the weight interval standard or not, and a signal for judging that the dishes accord with the weight interval standard is fed back to the dynamic camera module;
step S33: after the dynamic camera module receives the signal, the face tracking of the dish-passing workers is stopped;
step S34: the data storage unit stores the image and transmits the data to the data analysis module through electric connection.
According to the above technical solution, the step S4 further includes the following steps:
step S41: the data analysis module analyzes the picture of each frame in the image, and marks the picture after the refraction effect occurs between the pupils of the workers and the dishes in each frame of the image;
step S42: after the data analysis module receives the image, recording start-stop time L of the worker serving dishes in the image;
step S43: obtaining a total refraction time E through summarization, and finally calculating to obtain a concentration value Q;
step S44: after the concentration value Q is obtained, the catering robot can be in the food delivery speed range Smin，Smax]And calculating to finally obtain a speed value S, and sending the dishes to the room of the consumer by the catering robot according to the calculated speed value S.
According to the above technical solution, the step S5 further includes the following steps:
step S51: after the data analysis module finishes working, the data matching unit can calculate the speed according to the data and trigger the client feedback unit;
step S52: the client feedback unit analyzes and judges according to the last client evaluation, judges whether the next meal delivery speed needs to be adjusted or not, and transmits data to the intelligent optimization unit through an electric signal;
step S53: after receiving the analysis result, the intelligent optimization unit increases or decreases the speed M on the basis of the current speed according to the result;
step S54: the speed execution unit determines the final speed according to the speed interval range and sends the dishes to the room of the consumer.
According to the above technical solution, the calculation formula of the pupil concentration value Q of the dish transfer in step S43 is as follows:
wherein Q is the pupil concentration value, E is the refraction frequency between the pupil of the staff passing the dish and the dish, T is the total frame number of the image duration, K is the conversion coefficient of the pupil concentration value, so the interval of the pupil concentration value Q is calculated to be [ Q [min，Qmax]When the refraction number value K is larger, the pupil concentration value of the worker who passes the dish is larger, and otherwise, the pupil concentration value is smaller.
According to the above technical solution, the calculation formula of the meal delivery speed S of the meal drinking robot in the step S44 is as follows:
s is the speed of the catering robot when delivering food, QmaxMaximum concentration value of the staff passing the dish, SmaxThe maximum value of the dish conveying speed of the catering robot is SminFor the minimum of food passing speed of food and beverage robot, when being concentrated on value Q more big, the velocity value S of food and beverage robot is less, and food and beverage robot passes the dish speed and can be very slow this moment, and on the contrary when being concentrated on value Q less, the velocity value S of food and beverage robot is big more, therefore food and beverage robot passes the dish speed and can be very fast.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, the sensing module, the state monitoring module, the data analysis module and the speed control module are arranged, so that the catering robot can control the speed by observing the concentration degree of workers in dish transferring, and the completeness of dishes in the dish transferring process is ensured as much as possible.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic diagram of the system module composition of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution: the utility model provides an automatic planning integrated service system based on artificial intelligence, including the response module, state monitoring module, data analysis module, the fast module of accuse, the response module is used for responding to the change that detects desktop weight and take place, and signal transmission who will accord with dish weight standard gives food and beverage robot, state monitoring module is used for monitoring staff face state when biography dish, state monitoring module and response module internet access, data analysis module is arranged in passing dish staff's pupil in the image and carries out the analysis, so that calculate the concentration value of staff when passing dish, data analysis module is connected with the state monitoring module electricity, the fast module of accuse is used for controlling the speed when food and beverage robot send meal, in order to guarantee the integrity of dish, the fast module of accuse is connected with data analysis module electricity.
The sensing module comprises a gravity detection module, a gravity analysis module and a signal transmission unit, the gravity detection module is used for detecting the change of gravity of a tabletop end for placing dishes, the gravity analysis module is used for judging whether the gravity change meets the weight interval standard of the dishes, the gravity analysis module is electrically connected with the gravity detection module, the signal transmission unit is used for meeting the weight of the dishes, the signal of the interval standard is transmitted to the catering robot through a network, so that the dynamic camera shooting function can be started in an auxiliary mode, the signal transmission unit is electrically connected with the gravity analysis module, the sensing module is mainly used for monitoring the change of the gravity on the tabletop, and the signal transmission function is realized.
The state monitoring module comprises a signal receiving unit, a dynamic camera module and a gravity sensing module, the signal receiving unit is used for receiving network signals and starting the camera function of the catering robot, the dynamic camera module is used for collecting facial images of workers in dish transferring, the dynamic camera function is electrically connected with the signal receiving function, the gravity sensing unit is used for sensing the weight of the workers when the workers place dishes on the catering robot and feeding back data to the state monitoring module, the gravity sensing unit is electrically connected with the dynamic camera module, the dynamic camera module comprises a face tracking unit and a data storage unit, the face tracking unit is used for shooting the faces of the workers in dish transferring, the data storage unit is used for storing the obtained face images, the data storage unit is electrically connected with the face tracking unit, and the state monitoring module is mainly used for the catering robot to shoot the faces of the workers in dish transferring, and the image is stored and then transmitted to the data analysis module.
The data analysis module comprises an image analysis module and a logic judgment unit, the image analysis module is used for analyzing the facial images of the workers who pass the dishes, the logic judgment unit is used for judging the states of the workers when passing the dishes, the logic judgment unit is electrically connected with the image analysis module, the image analysis module comprises a time reading unit and a pupil tracking unit, the time reading module is used for reading the starting and ending time L of the workers who send the dishes in the images, the pupil tracking unit is used for tracking the pupil change of the workers when passing the dishes, the data analysis module is mainly used for analyzing the pupil change of the workers when passing the dishes in the images, and the starting and ending time L of the end dishes is recorded.
The speed control module comprises a data matching unit and a speed execution unit, the data matching unit is used for matching proper dish transmission speed according to the state of a worker, the speed execution unit is used for executing the dish transmission speed of the catering robot and is electrically connected with the data matching unit, the speed control module is mainly used for adjusting the dish sending speed of the catering robot according to the result of data analysis, the data matching unit comprises a client feedback unit and an intelligent optimization unit, the client feedback unit is used for analyzing client feedback, the intelligent optimization unit is used for finely adjusting the current speed, and the intelligent optimization unit is electrically connected with the client feedback unit.
The operation method of the automatic planning integrated service system based on artificial intelligence comprises the following steps:
step S1: after the consumer successfully places an order, the staff prepares dishes according to the menu and puts the dishes on a desktop with an induction module;
step S2: when a worker starts dishes from the desktop end with the sensing module, the desktop end with the sensing module sends a signal to the catering robot, and the catering robot starts to work;
step S3: a state monitoring module of the catering robot end is started to shoot and collect the face state of the current worker;
step S4: the catering robot can analyze the collected data, judge the state of the staff when the dish is delivered by analyzing the pupils of the staff delivering the dish and taking the time of the staff when the dish is delivered as a basis, adjust the speed of the catering robot when the dish is delivered according to the state of the staff when the dish is delivered, and deliver the dish to the room of a consumer;
step S5: the catering robot further optimizes the speed according to the feedback of the client, and finally sends dishes to a room of a consumer.
Step S3 further includes the steps of:
step S31: after the catering robot receives the signal sent by the induction module, the dynamic camera module starts to work to track the face of a worker who passes dishes;
step S32: when a worker places dishes on the catering robot, the gravity sensing module is triggered, the gravity sensing module can judge whether the dishes accord with the weight interval standard or not, and a signal for judging that the dishes accord with the weight interval standard is fed back to the dynamic camera module;
step S33: after the dynamic camera module receives the signal, the face tracking of the dish-passing workers is stopped;
step S34: the data storage unit stores the image and transmits the data to the data analysis module through electric connection.
Step S4 further includes the steps of:
step S41: the data analysis module analyzes the picture of each frame in the image, and marks the picture after the refraction effect occurs between the pupils of the workers and the dishes in each frame of the image;
step S42: after the data analysis module receives the image, recording start-stop time L of the worker serving dishes in the image;
step S43: obtaining a total refraction times E through summarization, and finally calculating a concentration value Q;
step S44: after the concentration value Q is obtained, the catering robot can be in the food delivery speed range Smin，Smax]And calculating to finally obtain a speed value S, and sending the dishes to the room of the consumer by the catering robot according to the calculated speed value S.
Step S5 further includes the steps of:
step S51: after the data analysis module finishes working, the data matching unit can calculate the speed according to the data and trigger the client feedback unit;
step S52: the client feedback unit analyzes and judges according to the last client evaluation, judges whether the next meal delivery speed needs to be adjusted or not, and transmits data to the intelligent optimization unit through an electric signal;
step S53: after receiving the analysis result, the intelligent optimization unit increases or decreases the speed M on the basis of the current speed according to the result;
step S54: the speed execution unit determines the final speed according to the speed interval range and sends the dishes to the room of the consumer.
The calculation formula of the pupil concentration value Q of the dish transfer in step S43 is:
wherein Q is the pupil concentration value, E is the pupil of the worker who passes the dishThe refraction times with dishes, T is the total frame number of the image duration, K is the conversion coefficient of the pupil concentration value, so that the interval of the pupil concentration value Q is calculated as [ Q ]min，Qmax]When the refraction number value K is larger, the pupil concentration value of the worker who passes the dish is larger, and otherwise, the pupil concentration value is smaller.
In step S44, the food delivery speed S of the food and drink robot is calculated as:
s is the speed of the catering robot when delivering food, QmaxMaximum concentration value of the staff passing the dish, SmaxThe maximum value of the dish conveying speed of the catering robot is SminFor the minimum of food passing speed of food and beverage robot, when being concentrated on value Q more big, the velocity value S of food and beverage robot is less, and food and beverage robot passes the dish speed and can be very slow this moment, and on the contrary when being concentrated on value Q less, the velocity value S of food and beverage robot is big more, therefore food and beverage robot passes the dish speed and can be very fast.
The first embodiment is as follows: after the order of the consumer is placed, the staff prepares the dish, places the dish on the desktop with gravity sensing, and the gravity detection module judges that the weight standard T of the dish is 120 × 30 3600 standard interval [100g, 1000g ] by detecting the weight of the dish]Then, the signal is sent to the catering robot, the catering robot starts a camera function, the camera tracks the face of the worker who passes the dish in a mode of 30 frames per second, the starting and stopping time of the worker who passes the dish is recorded, the refraction frequency E between the pupil of the worker who passes the dish and the dish is 3600, the time L of the worker who passes the dish is 120 seconds, the conversion coefficient K of the concentration value is 100, the total frame number T of the image is 120 multiplied by 30 to 3600 frames, the refraction frequency E between the pupil of the worker who passes the dish and the dish is 600 times, and the value is 600 times of the concentration value
The speed interval of the catering robot during dish delivery is known to be [5, 20 ]]Concentration interval of [0, 100 ]]Has already been preparedKnowing that the quality of the dishes fed back by the client is normal, the intelligent optimization unit further optimizes the speed, knowing that the value M is 1, the speed of the catering robot during dish delivery
Meter per second, the final catering robot takes dishes to the consumer's room at a speed of 6 meters per second.
The second embodiment: after the order placement of the consumer is completed, the worker prepares the dish, places the dish on a desktop with gravity sensing, and the gravity detection module judges that the weight standard interval [100g, 1000g ] of the dish is met by detecting the weight of the dish]Then, the signal is sent to the catering robot, the catering robot starts a camera shooting function, the camera tracks the face of a dish-passing worker in a mode of 30 frames per second, the starting and stopping time of dish passing of the worker is recorded, the refraction frequency E between the pupil of the dish-passing worker and a dish is known to be 36 times, the dish-passing time is L120 seconds, the conversion coefficient K of the concentration value is 100, the total frame number T of the image is 120 multiplied by 30 to 3600 frames, and the concentration value is 3600 frames
The speed interval of the known catering robot is [5, 20 ]]Concentration interval of [0, 100 ]]If the quality of the dishes fed back by the client is normal, the intelligent optimization unit further optimizes the speed, and if the M value is 1, the speed of the catering robot during dish delivery is known
Meter per second, since the catering robot speed is 20 meters per second maximum, the catering robot finally delivers dishes to the consumer's room at a speed of 20 meters per second.
The third embodiment is as follows: after the order placement of the consumer is completed, the worker prepares the dish, places the dish on a desktop with gravity sensing, and the gravity detection module judges that the weight standard interval [100g, 1000g ] of the dish is met by detecting the weight of the dish]Then, the signal is sent to the catering robot, the catering robot starts a camera shooting function, and the camera adopts a mode of 30 frames per second to carry the dishTracking the face of a person, recording the starting and ending time of dish transmission of the worker, knowing that the refraction frequency E between the pupil of the worker and the dish for dish transmission is 1800 times, the time L for dish transmission is 120 seconds, the conversion coefficient K of concentration value is 100, the total frame number T of the image is 120 multiplied by 30 to 3600 frames, and the concentration value
The speed interval of the known catering robot is [5, 20 ]]Concentration interval of [0, 100 ]]If the quality of the dish fed back by the client is abnormal, the intelligent optimization unit further optimizes the speed, and if the value M is 1, the speed of the catering robot during dish delivery is increased
Meter per second, the final catering robot takes dishes to the consumer's room at a speed of 11.5 meters per second.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The utility model provides an integrated service system of automatic planning based on artificial intelligence, includes response module, state monitoring module, data analysis module, accuse fast module, its characterized in that: the sensing module is used for sensing the start-stop time of dish serving of a detection worker, the state monitoring module is used for monitoring the facial state of the worker when serving dishes, the state monitoring module is connected with the sensing module through a network, the data analysis module is used for analyzing the state of the worker when serving dishes, the data analysis module is electrically connected with the state monitoring module, the speed control module is used for controlling the speed of the catering robot when serving dishes, and the speed control module is electrically connected with the data analysis module.
2. The system of claim 1, wherein the system comprises: the sensing module comprises a gravity detection module, a gravity analysis module and a signal transmission unit, wherein the gravity detection module is used for detecting the change of the gravity of the tabletop end for placing dishes, the gravity analysis module is used for judging whether the gravity change accords with the weight interval standard of the dishes, the gravity analysis module is electrically connected with the gravity detection module, the signal transmission unit is used for transmitting the signal which accords with the weight interval standard of the dishes to the catering robot through a network, and the signal transmission unit is electrically connected with the gravity analysis module.
3. The system of claim 2, wherein the system comprises: the state monitoring module comprises a signal receiving unit, a dynamic camera module and a gravity sensing module, the signal receiving unit is used for receiving network signals and starting the food and beverage robot camera shooting function, the dynamic camera shooting module is used for collecting facial images of a single worker during food delivery, the dynamic camera shooting function is electrically connected with the signal receiving function, the gravity sensing unit is used for sensing the weight of the staff when the staff places dishes on the catering robot, and feeds back data to the state monitoring module, the gravity sensing unit is electrically connected with the dynamic camera module, the dynamic camera module comprises a face tracking unit and a data storage unit, the face tracking unit is used for shooting the face of a dish-passing worker, the data storage unit is used for storing the acquired face image, and the data storage unit is electrically connected with the face tracking unit.
4. The system of claim 3, wherein the service system comprises: the data analysis module comprises an image analysis module and a logic judgment unit, the image analysis module is used for analyzing facial images of workers who pass dishes, the logic judgment unit is used for judging the state of the workers when the workers pass dishes, the logic judgment unit is electrically connected with the image analysis module, the image analysis module comprises a time reading unit and a pupil tracking unit, the time reading module is used for reading the starting and ending time of the workers when the workers send dishes in the images, the pupil tracking unit is used for tracking the pupil change of the workers when the dishes are passed, the speed control module comprises a data matching unit and a speed execution unit, the data matching unit is used for matching proper dish passing speed, the speed execution unit is used for executing the dish passing speed of the robot, the speed execution unit is electrically connected with the data matching unit, and the data matching unit comprises a client feedback unit and an intelligent catering optimization unit, the client feedback unit is used for analyzing client feedback, the intelligent optimization unit is used for finely adjusting the current speed, and the intelligent optimization unit is electrically connected with the client feedback unit.
5. The system of claim 4, wherein the service integration system comprises: the operation method of the automatic planning integrated service system based on artificial intelligence comprises the following steps:
step S1: after the consumer successfully places an order, the staff prepares dishes according to the menu and puts the dishes on a desktop with an induction module;
step S2: when a worker starts dishes from the desktop end with the sensing module, the desktop end with the sensing module sends a signal to the catering robot, and the catering robot starts to work;
step S3: the method comprises the following steps that a state monitoring module of the catering robot is started, and the face state of a current worker is shot and collected;
step S4: the catering robot can analyze the acquired data, judge the state of the staff when the dish is delivered by analyzing the pupils of the staff delivering the dish and taking the time of the staff during the dish delivering process as a basis, and adjust the speed of the catering robot according to the state of the staff when the dish is delivered;
step S5: the catering robot further optimizes the speed according to the feedback of the client, and finally sends dishes to a room of a consumer.
6. The system of claim 5, wherein the service system comprises: the step S3 further includes the steps of:
step S31: after the catering robot receives the signal sent by the induction module, the dynamic camera module starts to work to track the face of a worker who passes dishes;
step S32: when a worker places dishes on the catering robot, the gravity sensing module is triggered, the gravity sensing module can judge according to whether the dishes meet the weight interval standard or not, and a signal for judging that the dishes meet the weight interval standard is fed back to the dynamic camera module;
step S33: after the dynamic camera module receives the signal, the face tracking of the dish-passing workers is stopped;
step S34: the data storage unit stores the image and transmits the data to the data analysis module through electric connection.
7. The system of claim 6, wherein the service integration system comprises: the step S4 further includes the steps of:
step S41: the data analysis module analyzes the picture of each frame in the image, and marks the picture after the refraction effect occurs between the pupils of the workers and the dishes in each frame of the image;
step S42: after the data analysis module receives the image, recording start-stop time L of the worker serving dishes in the image;
step S43: obtaining a total refraction times E through summarization, and finally calculating a concentration value Q;
step S44: after obtaining the concentration value Q, the catering robot can be in the meal delivery speed range Smin，Smax]And calculating to finally obtain a speed value S, and sending the dishes to the room of the consumer by the catering robot according to the calculated speed value S.
8. The system of claim 7, wherein the service integration system comprises: the step S5 further includes the steps of:
step S51: after the data analysis module finishes working, the data matching unit can calculate the speed according to the data and trigger the client feedback unit;
step S52: the client feedback unit analyzes and judges according to the last client evaluation, judges whether the next meal delivery speed needs to be adjusted or not, and transmits data to the intelligent optimization unit through an electric signal;
step S53: after receiving the analysis result, the intelligent optimization unit increases or decreases the speed M on the basis of the current speed according to the result;
step S54: the speed execution unit determines the final speed according to the speed interval range and sends the dishes to the room of the consumer.
9. The system of claim 8, wherein the service integration system comprises: the calculation formula of the pupil concentration value Q of the dish transfer in the step S43 is as follows:
wherein Q is the pupil concentration value, E is the refraction frequency between the pupil of the staff passing the dish and the dish, T is the total frame number of the image duration, K is the conversion coefficient of the pupil concentration value, so the interval of the pupil concentration value Q is calculated to be [ Q [min，Qmax]When the refraction number value K is larger, the pupil concentration value of the worker who passes the dish is larger, and otherwise, the pupil concentration value is smaller.
10. The system of claim 9, wherein the service integration system comprises: the food delivery speed S of the food drinking robot in the step S44 is calculated according to the formula:
s is the speed of the catering robot when delivering food, QmaxFor maximum concentration value of the staff passing the dish, SmaxThe maximum value of the dish conveying speed of the catering robot is SminFor the minimum of food passing speed of food and beverage robot, M is food and beverage robot intelligent optimization 'S speed, when being concentrated on value Q when big, food and beverage robot' S velocity value S is less, and food and beverage robot passes the dish speed this moment and can be very slow, and on the contrary when being concentrated on value Q when little, food and beverage robot 'S velocity value S is big more, therefore food and beverage robot' S dish passing speed can be very fast.
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