Computerized systems and methods for preparing food autonomously

Abstract

A method for performing tasks in the autonomous system for preparing a food product, the method comprises identifying that a process is required to be performed as part of preparing the food product; converting the process to multiple tasks, wherein the tasks require different tangible devices; sending the multiple tasks to a pipeline queue configured to manage the tasks on a first-in-first-out (FIFO) basis; when a specific task of the multiple tasks reaches a beginning of the pipeline queue, sending the task to a manager queue controlled by a task manager, wherein the task manager is coupled to one of the different tangible devices; when the specific task reaches the beginning of the manager queue, sending the specific task to a relevant tangible device for execution; executing the task.

Description

[0001] COMPUTERIZED SYSTEMS AND METHODS FOR PREPARING FOOD AUTONOMOUSLY

[0002] FIELD OF THE INVENTION

[0003] The present invention relates to computerized systems and processes for preparing food and methods for utilizing it.

[0004] BACKGROUND OF THE INVENTION

[0005] The concept of restaurants as a place for providing meals or cooked food for people has been known for centuries. Cooked food is defined as food ready to be consumed by the end-user, after being fried, baked, mixed, heated, boiled, or otherwise prepared.

[0006] Restaurants provide a cultural experience, in which the customers have to go to a certain place, dress nicely, and be served by waiters. This may take more time than required by the customers, and incur additional costs, such as transportation. In addition, it is fairly expensive to operate a restaurant in a central location, in terms of rental payments, indoor design, labor costs, and the like. Therefore, there is a mutual benefit for both customers and restaurant owners to transfer some of the traffic to delivery. One should remember that the restaurant’ s income is limited by its size, while the delivery is limited by the staff s ability to produce food, which is much higher and flexible. Staff s capacity to produce cooked food has been extended in recent years through the development of ghost kitchen (also known as a delivery-only restaurant, virtual kitchen, shadow kitchen, commissary kitchen, or dark kitchen), which is a professional food preparation and cooking facility set up for the preparation of delivery-only meals.

[0007] Yet, ghost kitchens require people to prepare cooked food, which becomes a significant cost component. In addition, the kitchen’s managers cannot accurately tell the exact number of cooks required each day / shift to provide the cooked food, which reduces the efficiency and profit of the ghost kitchen. SUMMARY OF THE INVENTION

[0008] The subject matter discloses a method for performing tasks in the autonomous system for preparing a food product, the method comprises identifying that a process is required to be performed as part of preparing the food product; converting the process to multiple tasks, wherein the tasks require different tangible devices; sending the multiple tasks to a pipeline queue configured to manage the tasks on a first-in-first-out (FIFO) basis; when a specific task of the multiple tasks reaches a beginning of the pipeline queue, sending the task to a manager queue controlled by a task manager, wherein the task manager is coupled to one of the different tangible devices; when the specific task reaches the beginning of the manager queue, sending the specific task to a relevant tangible device for execution; executing the task.

[0009] In some cases, the method further comprises reporting to the management unit that the task was executed. In some cases, the reporting is performed using a sensor located in the autonomous system. In some cases, the reporting is performed using a controller coupled to the physical device that executed the task

[0010] In some cases, at least some of the tasks in the process are required to be performed serially. In some cases, the task manager is coupled to multiple tangible devices capable of executing a task of a specific type. In some cases, the task manager may hold tasks associated with different processes. In some cases, the manager queue assigns a location for the specific task according to a task location. In some cases, the method further comprises preventing collision between moving objects in the autonomous system for preparing the food product.

[0011] BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Some embodiments of the invention are herein described, by way of example only, with reference to the accompanying drawings. With specific reference now to the drawings in detail, it is stressed that the particulars shown are by way of example and for purposes of illustrative discussion of embodiments of the invention. In this regard, the description taken with the drawings makes apparent to those skilled in the art how embodiments of the invention may be practiced.

[0013] In the drawings: Figure 1 shows a perspective view of an autonomous system for preparing a pizza, according to exemplary embodiments of the present invention.

[0014] Figure 2 shows computerized components of the autonomous system for preparing a pizza, according to exemplary embodiments of the subject matter.

[0015] Figure 3 shows a computerized architecture for performing tasks in the autonomous system for preparing food products, according to exemplary embodiments of the subject matter.

[0016] Figure 4 shows a method for performing tasks in the autonomous system for preparing food products, according to exemplary embodiments of the subject matter.

[0017] Figure 5 shows a method for preventing collision between moving objects in the autonomous system for preparing food products, according to exemplary embodiments of the subject matter.

[0018] Figure 6 shows a method of identifying characteristics of dough using image processing techniques, according to exemplary embodiments of the subject matter.

[0019] DETAILED DESCRIPTION OF THE INVENTION

[0020] The subject matter discloses an autonomous system for preparing food products, computerized architectures for controlling the processes performed in the autonomous system and the controlling processes. The autonomous system comprises physical components such as ingredients tanks that contain the ingredients of the food products, heating and cooking equipment for preparing the food products from the ingredients, a computerized unit for controlling the cooking and delivering process, and robotic units for moving objects in the system from one place to another. The system comprises controllers coupled to the physical components, for example, programmable logic controllers (PLCs). The PLCs receive commands from the management unit of the autonomous system and operate accordingly.

[0021] The term “autonomous” is defined in the subject matter as self-governing, that does not require persons to operate. This is different from automated, which performs a process but still requires persons to operate it. The autonomous system cooks the food products from the ingredients of the food products, the ingredients are stored in the system’s ingredients tanks in a cooled state, or a frozen state, in a temperature range of -18-10 degrees Celsius, more specifically about -18 to 4 degrees Celsius. The food product may be pizza, meat-based courses such as burgers and steaks, courses that include rice, courses that include noodles, sandwiches, salads, and the like.

[0022] Figure 1 shows a perspective view of an autonomous system for preparing a pizza, according to exemplary embodiments of the present invention.

[0023] The perspective view does not show the sidewalls and ceiling of the housing, only the floor 100. The edges 102 of the floor 100 define the walls from which the sidewalls extend upwards. The volume defined inside the housing is divided into at least two (2) sub-areas defined by a wall 145 or another barrier that prevents the passage of cold air from the cooled sub-area to the noncooled area. The cooled area comprises the first array of ingredients tanks 110 and the second array of ingredients tanks 120, both containing the ingredients used to cook the pizza, or dishes, per the orders received in the system. The first array of ingredients tanks 110 may be implemented in the form of cabinets having doors. When wishing to use the ingredients from the ingredients tanks 110, the relevant cabinet is moved towards the makeline 135. The cooled area may also include the makeline 135, which is where the pizza is assembled from the ingredients. In some other cases, the makeline 135 is located in the non-cooled area. The cooled area also comprises the loading area 130. The loading area may span in one of the ends of the housing, to enable filling the ingredients tanks in a minimally invasive manner, for example by opening a door or a window in the housing sidewall, and accessing the ingredients tanks to be filled.

[0024] The computerized unit governing the operation of the autonomous system receives an indication as to the ingredients inputted into the ingredients tanks. Such information may be inputted by the supplying person into an electronic device. In other cases. The ingredients are secured to a plate having an RFID tag that identifies the type of ingredient just inserted into an ingredients tank, or to a specific shelf in a cabinet, as in the first array of ingredients tanks 110. In the second array of ingredients tanks 120, the indication may be provided by a weight sensor detecting the weight on each cartridge and communicating with the computerized unit.

[0025] The makeline 135 comprises one or more moving arms and conveyors for preparing the pizza. For example, in case the pizza is a pizza plate, the arms extract the pizza dough from a specific cabinet of the first array of ingredients tanks 110, and move the dough under relevant cartridges in the second array of ingredients tanks 120, to spread sauces and add toppings. The arms of the makeline 135, and the arrangement of the cartridges in the second array of ingredients tanks 120, enable to pour sauce, cheese, and toppings on multiple doughs concurrently. After the dough is covered with toppings and sauces according to the order, the arm moves the dough to a pre-oven area 140, coupled to a conveyor. The conveyor moves the dough to an oven 150.

[0026] Figure 2 shows computerized components of the autonomous system for preparing a pizza, according to exemplary embodiments of the subject matter.

[0027] The autonomous system comprises a processor 210. The processor 210 is configured to manage the processes performed by the autonomous system, such as receive orders, prepare the food products, pack the products and the like. The processor 210 is configured to send signals to other components of the autonomous system, for example to controllers 240 coupled to the physical components of the autonomous system, such as robots, refrigerators, ovens and the like. The processor 210 may be a general -purpose processor, a microprocessor, or any other type of processor.

[0028] The autonomous system comprises a communication unit 220 configured to communicate with devices and / or machines located inside and / or outside the autonomous system. The communication unit 220 may receive orders over the internet or a cellular network. The communication unit 220 may receive authentication signals from persons collecting the ordered food items, for example over a Bluetooth protocol. The communication unit 220 may send signals to remote devices after receiving a command from a processor 210 in response to events, such as the consumption of goods in the containers, technical problems, abnormal measurements from sensors, and the like.

[0029] The autonomous system comprises memory 230 configured to store information. The memory 230 may store a set of rules required to perform tasks in the autonomous system. The memory 230 may store data related to customers, such as prior purchases, addresses, contact details, and the like. The memory 230 may store rules related to the maintenance of the autonomous system, such as a list of events that activate a physical device. For example, in case a humidity sensor collects a measurement that is higher than a threshold, activate a cleaning unit. The autonomous system comprises device controllers 240 coupled to the physical devices of the autonomous system. The controllers 240 are configured to receive commands or signals from another device, for example from the processor 210 or other devices, and cause the physical device to perform a task. The task can comprise multiple sub-tasks, such as moving, collecting, heating, activating a sub-unit in the physical device, and the like. For example, a task can be “open a refrigerator door”.

[0030] The autonomous system comprises sensor unit 250 configured to collect sensor measurements. The sensors may be located inside the autonomous system or in the vicinity of the autonomous system housing. The sensors may include image sensors such as cameras, temperature sensors, humidity sensors, gas sensors, sensors configured to detect the presence of materials or compounds, volume sensors, and additional sensors desired by a person skilled in the art. In some cases, the sensors included in the sensor unit 250 send measurements to the processor 210, or process the measurements locally and send signals only in case the collected measurements exceed a threshold or satisfy a rule. In some cases, the sensors included in the sensor unit 250 are coupled to a power unit such as a battery, a power generator, or an electric grid.

[0031] The autonomous system comprises order unit 260 configured to manage orders to the autonomous system. The order unit 260 receives order details such as the number and type of food products, verifies that the payment is valid, and optionally sends a message to the person collecting the order.

[0032] The autonomous system comprises inventory manager 270 configured to manage the inventory. The inventory manager 270 has access to the orders database and can compute the amount of ingredients used over some time. The inventory manager 270 also receives a list or a total amount of food items in which a specific container was used in order to compute a current ingredient quantity in the specific container. The inventory manager 270 may also be configured to predict data in which the amount of ingredients in the specific container will be lower than a threshold based on known order patterns, such as 200 orders a day divided into different pizza types.

[0033] Figure 3 shows a computerized architecture for performing tasks in the autonomous system for preparing food products, according to exemplary embodiments of the subject matter. The architecture comprises pipeline queues 310, 320, 330 configured to manage tasks of a specific process. Each pipeline queue comprises multiple queues, for example, one queue for a task in the process. For example, pipeline queue 310 comprises queues 311, 312, 313, 314, pipeline queue 320 comprises queues 321, 322, 323, 324 and pipeline queue 330 comprises queues 331, 332, 333, 334. The tasks from the pipeline queues 310, 320, 330 are sent over a communication bus 340 to managers of physical devices. The managers may include dough manager 350 configured to manage the operation of robots 351 , 352, 353, 354. Another exemplary manager is topping manager 360 configured to manage the operation of robots 361, 362, 363, 364, and hot robot manager 370 configured to manage the operation of robots 371 , 372, 373, 374. In some cases, the pipeline queues execute the tasks synchronously, while the managers 350, 360 and 370 perform the tasks asynchronously, according to a task priority.The managers 350, 360, 370 can manage multiple tasks performed concurrently, for example one task by robot 351, another task by robot 352 and another task by robot 354. The tasks arrive at the manager in a sequential manner but can be performed in parallel according to physical limitations of the devices controlled by the manager.

[0034] When a process is required to be performed, the process is defined to include multiple steps. Each step runs commands in a sequential order, but each step runs in parallel. Each command can run sequential or parallel sub commands.

[0035] The task moves between steps using a queue that does not consider a priority value. The tasks are performed in the queues according to the order in which they arrive - first in first out(FIFO).

[0036] Figure 4 shows a method for performing tasks in the autonomous system for preparing food products, according to exemplary embodiments of the subject matter.

[0037] Step 410 discloses identifying that a process is required to be performed. The process may be preparing a food item, cleaning a component in the system, preparing dough to be ready for baking, and the like.

[0038] Step 420 discloses converting the process to multiple tasks. The conversion may be done based on a set of rules stored in the memory. For example, in case the process is “preparing a medium-sized pizza with mushrooms topping”, the tasks include extracting dough from a cabinet, moving the dough to a sauce dispenser, dispensing the sauce while rotating the dough, moving the dough to a cheese dispenser and the like. In some cases, at least some of the tasks in a specific process are required to be performed serially, meaning that the fifth task can only be done after tasks 1-4 are completed. The tasks may require different tangible devices, such as a robotic arm, oven, container door, and the like.

[0039] Step 430 discloses receiving a new task at a pipeline queue. The tasks are received at the pipeline queue in the order they arrive, first-in-first-out (FIFO). The pipeline queue is defined as a queue configured to hold the tasks for a specific process. For example, the pipeline queue receives 6 tasks for preparing and packing 2 pizzas, as this process requires a robotic arm and two ovens.

[0040] Step 440 discloses a case in which atask reaches the beginning of the pipeline queue. Then, the task is sent to the relevant task manager. The manager is coupled to a device capable of performing one or more tasks of a certain type. The manager may be coupled to multiple devices, for example, manager #1 is coupled to 5 robotic arms in the makeline area, manager #2 is coupled to the container doors, manager #3 is coupled to the topping dispensers, and the like. The managers hold queues of the tasks.

[0041] Step 450 discloses a case in which the task is assigned a location in a manager queue of the relevant manager according to the task’s priority. The task manager may hold tasks associated with different processes, each task may have a priority value according to urgency, business value, postponing other tasks, and the like.

[0042] Step 460 discloses a case in which the task reaches the beginning of the relevant manager queue. Then, the task is sent to the relevant physical component for execution. The task may be sent using a short message with the task’s identifier, by applying an electric voltage that matches the task and the like.

[0043] Step 470 discloses the execution of the task. For example, moving the item to a target location, dispensing ingredients for a specific time duration, activating the oven, and the like. Step 480 discloses reporting to the management unit that the task was executed. The reporting may be done using a sensor of the sensor unit, for example by capturing an image, using a controller coupled to the physical device that executed the task, or using another technique desired by a person skilled in the art.

[0044] Figure 5 shows a method for preventing collision between moving objects in the autonomous system for preparing food products, according to exemplary embodiments of the subject matter. Step 510 discloses the robot receiving a command to move an item. The command may be received over a wireless channel, such as a Wi-Fi network, to a controller coupled to the robot. The command comprises an identifier of the item’s location, for example, “shelf #4 on cabinet #2” or “move 3.2 meters to the right and 0.8 meters upward”. The command also comprises a destination of the item, for example, an oven or plate located at a certain location in the makeline area.

[0045] Step 520 discloses themanagement unit marks areas as busy according to the command. The areas include the paths in which the robot moves along the task - the first path is from the robot’s original location to the item’s location and from the item’s location to the destination. In some cases, the areas include the path from the destination to the robot’s docking station.

[0046] Step 530 discloses the robot moving to the item’s location. The robot may move along a track, along a pole, on a surface, may fly, or a combination of the above. The robot may send a signal to the management unit indicating the presence of the robot at the item’s location, meaning that the management unit can remove the path from the robot’s original location to the item’s location from a list of occupied areas, enabling other devices to travel in the vacant areas.

[0047] Step 540 discloses the robot coordinating with a door protecting the item. For example, in case the robot is required to collect an item from a cabinet and the cabinet’s door is closed, the robot sends a message to open the door. The message may be sent via the management unit or directly to the door’s controller. In case the opening movement of the door interferes with the robot’s movement towards the item, the robot waits to receive a confirmation message that the door is open and only then approaches the item.

[0048] Step 550 discloses the robot collecting the item. The robot may collect the item using gripping arms, by placing the item on a surface on the robot’s body, by placing the item on a plate or other movable surface carried by the robot, and the like.

[0049] Step 560 discloses the robot carrying the item to item’s destination. The destination may be included in the command sent to the robot in step 510 or may be sent after the robot collects the item. Step 570 discloses the robot placing the item on the destination. The robot may place the item on a plate, in an oven, onto another device, inside a container or cabinet and the like.

[0050] Step 580 discloses the robot updating management unit after the execution of steps. The update may be sent over a wireless channel or using another technique desired by a person skilled in the art, such as scanning a code installed on the robot’s arms versus a scanner located at the destination.

[0051] Step 590 discloses the management unit marks areas as vacant after the execution of steps in the task. For example, after reaching the item’s location, mark the area between the robot’s original location and the item’s location as vacant. Similarly, after reaching the destination, mark the area between the item’s location and the destination as vacant.

[0052] Figure 6 shows a method of identifying characteristics of dough using image processing techniques, according to exemplary embodiments of the subject matter.

[0053] Step 600 discloses collecting images of the dough. The images may be grayscale, infra-red, RGB images, or other images selected by a person skilled in the art. The images may be taken from multiple cameras located at multiple directions relative to the dough.

[0054] Step 605 discloses applying a perspective correction process in order to measure correctly and consistently. The correction may change values of the dots’ locations according to the location / direction of the camera relative to the dough location, or relative to the location of the specific dot or area of the dough.

[0055] Step 610 discloses sampling one of the areas of the dough and computing an average position of dots in the area. In some cases, the surface may be sampled for multiple positions where a specific dot is shown in the collected images.

[0056] Step 620 discloses computing gradients in the dough included in the images. The gradients are defined as changes in heights between points in the images that represent different areas in the dough. In some cases, the computed gradients are translated to a quality score of the dough. The quality score may then be compared to thresholds to determine whether the dough is valid and can be provided to the customer or not.

[0057] Step 630 discloses mapping pixel displacement configured to enable measurement of heights relative to similar points on the same surface. In some cases, the absolute height of the surface is required, and the method comprises projecting an additional feature in order to fix the measurement’s base. For example, projecting a simple line across the dough and the base surface (table or gripper) enables measuring of surface displacement relative to the reference plane. The surface displacement may be calculated based on actual line displacement between planes. In some exemplary cases, the autonomous system of the subject matter may use artificial intelligence techniques for the following processes: 1. Detecting abnormal wear / load from sensors.

[0058] 2. At the process level - calibrate the dough opening position according to the dough temperature.

[0059] 3. Changing process times, for example, the dough's swelling time.

[0060] In some exemplary cases, the autonomous system of the subject matter may use imaging systems for the following processes: 1. QA of the food products after preparation. 2. Testing the dough - is it the right height, the right color, and the right diameter. 3. To cut the pizza at desired locations that match the toppings.

[0061] Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications, and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications, and variations that fall within the spirit and broad scope of the appended claims.

[0062] All publications, patents, and patent applications mentioned in this specification are herein incorporated in their entirety by reference into the specification, to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated herein by reference. In addition, citation or identification of any reference in this application shall not be construed as an admission that such reference is available as prior art to the present invention. To the extent that section headings are used, they should not be construed as necessarily limiting.

Claims

CLAIMS:

1. A method for performing tasks in the autonomous system for preparing a food product, the method comprises: identifying that a process is required to be performed as part of preparing the food product; converting the process to multiple tasks, wherein the tasks require different tangible devices; sending the multiple tasks to a pipeline queue configured to manage the tasks on a first- in-first-out (FIFO) basis; when a specific task of the multiple tasks reaches a beginning of the pipeline queue, sending the task to a manager queue controlled by a task manager, wherein the task manager is coupled to one of the different tangible devices; when the specific task reaches the beginning of the manager queue, sending the specific task to a relevant tangible device for execution; executing the task.

2. The method of claim 1 , further comprises reporting to the management unit that the task was executed.

3. The method of claim 2, wherein the reporting is performed using a sensor located in the autonomous system.

4. The method of claim 2, wherein the reporting is performed using a controller coupled to the physical device that executed the task5. The method of claim 1, wherein at least some of the tasks in the process are required to be performed serially.

6. The method of claim 1 , wherein the task manager is coupled to multiple tangible devices capable of executing a task of a specific type.

7. The method of claim 1, wherein the task manager may hold tasks associated with different processes.

8. The method of claim 1, wherein the manager queue assigns a location for the specific task according to a task location.

9. The method of claim 1, further comprises preventing collision between moving objects in the autonomous system for preparing the food product.

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