Robot control method, device, computer equipment, and medium

Abstract

The embodiment of the present application discloses a robot control method, device, computer equipment, and medium, which includes: when there are dishes on a tray rack, photographing the dishes through a camera to obtain a dish image; determining the target dish name and target attribute information corresponding to the dish image; determining the dining table number corresponding to the target dish name and target attribute information to obtain m dining table numbers; obtaining the order time corresponding to the m dining table numbers to obtain m order times; determining the earliest order time among the m order times to obtain the target dining table number corresponding to the earliest order time; obtaining the destination position of the target dining table number and obtaining the current position of the food delivery robot; generating a navigation route between the current position and the destination position; and controlling the food delivery robot to deliver the dishes to the destination position along the navigation route. The use of the embodiment of the present application can improve the food delivery efficiency and accuracy of the food delivery robot.

Description

Technical Field

[0001] The present application relates to the field of robotics technology, and in particular to a robot control method, device, computer equipment, and medium. Background Art

[0002] With the rapid development of science and technology, technology is gradually changing people's lives. Among them, robots are also being used in life. At present, the function of robot delivery is relatively simple, and it often requires strict instructions from users to deliver the dishes to the designated location, for example, delivering the dishes to table number xx. Therefore, how to improve the efficiency and accuracy of the food delivery robot needs to be solved urgently. Summary of the invention

[0003] The embodiments of the present application provide a robot control method, device, computer equipment, and medium, which can improve the food delivery efficiency and accuracy of the food delivery robot.

[0004] In a first aspect, an embodiment of the present application provides a robot control method, which is applied to a food delivery robot, wherein the food delivery robot includes a tray rack and a camera, and the method includes:

[0005] Detecting whether there are dishes on the tray rack;

[0006] When there are dishes on the tray rack, the dishes are photographed by the camera to obtain a dish image;

[0007] Determine a target dish name and target attribute information corresponding to the dish image, wherein the target attribute information includes at least one of the following: portion, plating method, color, and quantity;

[0008] Determine the dining table number corresponding to the target dish name and the target attribute information, and obtain m dining table numbers, where m is a positive integer;

[0009] Obtain the order time associated with the m dining table numbers to obtain m order times;

[0010] Determine the earliest order time among the m order times, and obtain the target dining table number corresponding to the earliest order time;

[0011] Obtain the destination location of the target dining table number and the current location of the food delivery robot;

[0012] generating a navigation route between the current location and the destination location;

[0013] The food delivery robot is controlled to deliver the food to the destination along the navigation route.

[0014] In a second aspect, an embodiment of the present application provides a robot control device, which is applied to a food delivery robot. The food delivery robot includes a tray rack and a camera. The device includes: a detection unit, a shooting unit, a determination unit, an acquisition unit, a generation unit and a control unit, wherein:

[0015] The detection unit is used to detect whether there are dishes on the tray rack;

[0016] The photographing unit is used to photograph the dishes through the camera to obtain dish images when there are dishes on the tray rack;

[0017] The determining unit is used to determine the target dish name and target attribute information corresponding to the dish image, wherein the target attribute information includes at least one of the following: portion, plating method, color, and quantity; determine the dining table number corresponding to the target dish name and the target attribute information, and obtain m dining table numbers, where m is a positive integer;

[0018] The acquisition unit is used to acquire the order time associated with the m dining table numbers to obtain m order times;

[0019] The determining unit is further configured to determine the earliest order time among the m order times, and obtain a target dining table number corresponding to the earliest order time;

[0020] The acquisition unit is further used to acquire the destination position of the target dining table number and the current position of the food delivery robot;

[0021] The generating unit is used to generate a navigation route between the current location and the destination location;

[0022] The control unit is used to control the food delivery robot to deliver the dishes to the destination location along the navigation route.

[0023] In a third aspect, an embodiment of the present application provides a computer device, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

[0024] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in the first aspect of the embodiment of the present application.

[0025] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0026] The implementation of the embodiments of the present application has the following beneficial effects:

[0027] It can be seen that the robot control method, device, computer equipment, and medium described in the embodiments of the present application are applied to a food delivery robot. The food delivery robot includes a tray rack and a camera. It detects whether there are dishes on the tray rack. When there are dishes on the tray rack, the dish is photographed by the camera to obtain a dish image, and the target dish name and target attribute information corresponding to the dish image are determined. The target attribute information includes at least one of the following: portion, plating method, color, and quantity. The dining table number corresponding to the target dish name and the target attribute information is determined, and m dining table numbers are obtained, where m is a positive integer. The order time for the m dining table numbers is obtained, and the m order times are obtained. , determine the earliest order time among m order times, obtain the target table number corresponding to the earliest order time, obtain the destination location of the target table number, obtain the current location of the food delivery robot, generate a navigation route between the current location and the destination location, and control the food delivery robot to deliver the dishes to the destination location along the navigation route. It can not only automatically identify the dishes, but also locate the earliest ordered table number based on the dish name and attribute information of the dishes. Furthermore, a navigation route is generated based on the current location of the food delivery robot and the destination location of the earliest ordered table number, and the food delivery is completed using the navigation route. In this way, the food delivery efficiency and accuracy of the food delivery robot can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 It is a flowchart of a robot control method provided in an embodiment of the present application;

[0030] Figure 2 is a flow chart of another robot control method provided in an embodiment of the present application;

[0031] Figure 3 is a structural schematic diagram of a computer device provided in an embodiment of the present application;

[0032] Figure 4 This is a block diagram of the functional units of a robot control device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0034] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0035] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0036] The embodiments of the present application are described in detail below.

[0037] See also Figure 1 , Figure 1 1 is a flow chart of a robot control method provided in an embodiment of the present application. As shown in the figure, the robot control method is applied to a food delivery robot. The food delivery robot includes a tray rack and a camera. The robot control method includes:

[0038] 101. Detect whether there are dishes on the tray rack.

[0039] In an embodiment of the present application, the food delivery robot includes a tray rack and a camera, and the camera can take pictures of the tray rack.

[0040] In a specific implementation, a camera can be used to detect whether there are dishes on the tray rack, that is, the dishes can be identified using image recognition technology.

[0041] Optionally, a weight sensor is provided below the tray rack, and the above step 101, detecting whether there are dishes on the tray rack, may include the following steps:

[0042] 11. Detecting the target weight of the objects placed on the pallet rack by the weight sensor;

[0043] 12. When the target weight is greater than a preset weight, it is determined that there are dishes on the tray rack.

[0044] The preset weight may be preset or set by system default.

[0045] In a specific implementation, a weight sensor can be provided under the tray rack, and the target weight of the objects placed on the tray rack is detected by the weight sensor. When the target weight is greater than the preset weight, it can be determined that there are dishes on the tray rack. Conversely, when the target weight is less than or equal to the preset weight, it can be confirmed that there are no dishes on the tray rack. When there are no dishes on the tray rack, the food delivery robot can be charged or wait for food to be delivered.

[0046] 102. When there are dishes on the tray rack, the dishes are photographed by the camera to obtain dish images.

[0047] In an embodiment of the present application, when there are dishes on the tray rack, the direction of the camera can be adjusted to aim the camera at the dishes and shoot them to obtain images of the dishes. In this way, the dishes can be automatically identified to facilitate subsequent dish delivery.

[0048] 103. Determine a target dish name and target attribute information corresponding to the dish image, wherein the target attribute information includes at least one of the following: portion, plating method, color, and quantity.

[0049] The target dish name can be understood as the name of the dish, and different dishes can correspond to different names. For example, the dish name can be braised fish, fish-flavored pork shreds, minced meat and eggplant, etc., which are not limited here.

[0050] In the embodiment of the present application, the attribute information includes at least one of the following: portion, plating method, color, quantity, etc., which are not limited here. The portion can be understood as the portion of the dish, for example, large portion, medium portion, small portion, etc., the color can be understood as the hue of the dish, the plating method describes the arrangement of the dish on the plate, and the quantity can be understood as the number of the same dish. One or more dishes can be placed on the tray rack.

[0051] 104. Determine the dining table number corresponding to the target dish name and the target attribute information, and obtain m dining table numbers, where m is a positive integer.

[0052] In the embodiment of the present application, the dining table number corresponding to the target dish name and the target attribute information can be determined through the ordering system to obtain m dining table numbers, where m is a positive integer.

[0053] Optionally, the above step 104, determining the dining table number corresponding to the target dish name and the target attribute information to obtain m dining table numbers, may include the following steps:

[0054] 41. Obtain order information from the order system, wherein the order information includes n order lists, each of which includes at least one ordered dish, each ordered dish corresponds to a dish name and attribute information, each order list corresponds to a dining table number, and n is a positive integer greater than or equal to m;

[0055] 42. Match the dish names and attribute information of the ordered dishes in the n order lists with the target dish name and the target attribute information to obtain k target ordered dishes, where k is a positive integer not less than m;

[0056] 43. Obtain the dining table numbers corresponding to the k target ordered dishes to obtain the m dining table numbers.

[0057] In a specific implementation, order information can be obtained from the ordering system, where the order information includes n order lists, each of which includes at least one ordered dish, each ordered dish corresponds to a dish name and attribute information, each order list corresponds to a dining table number, and n is a positive integer greater than or equal to m. The dish names and attribute information of the ordered dishes in the n order lists are then matched with the target dish name and the target attribute information to obtain k target ordered dishes, where k is a positive integer not less than m. The dining table numbers corresponding to the k target ordered dishes are obtained to obtain m dining table numbers. In this way, not only can dishes be recognized by image, but the corresponding dining table numbers can also be located based on the recognized dishes.

[0058] 105. Obtain the order time associated with the m dining table numbers to obtain m order times.

[0059] In a specific implementation, different dining table numbers may correspond to different order times, and then the order times corresponding to m dining table numbers may be obtained to obtain m order times.

[0060] 106. Determine the earliest order time among the m order times, and obtain a target dining table number corresponding to the earliest order time.

[0061] In the specific implementation, the earliest order time among the m order times can be determined, and the target table number corresponding to the earliest order time can be obtained. In this way, the table number corresponding to the earliest order time corresponding to the identified dish can be located, which is convenient for the subsequent dish delivery destination positioning.

[0062] 107. Obtain the destination location of the target dining table number and obtain the current location of the food delivery robot.

[0063] In the embodiment of the present application, different dining table numbers may correspond to different locations, and thus, the destination location of the target dining table number may be obtained, and the current location of the food delivery robot may also be obtained through indoor positioning technology (wireless fidelity (Wi-Fi)).

[0064] 108. Generate a navigation route between the current location and the destination location.

[0065] In a specific implementation, a path planning algorithm may be used to generate a navigation route between the current location and the destination location.

[0066] 109. Control the food delivery robot to deliver the food to the destination along the navigation route.

[0067] In an embodiment of the present application, the food delivery robot can be controlled to deliver dishes to a destination along a navigation route, thereby improving the food delivery efficiency and accuracy of the food delivery robot.

[0068] Optionally, the food delivery robot further includes a food protection device and a sensor, and may further include the following steps:

[0069] A1. Obtaining reference control parameters of the dish protection device corresponding to the target dish name;

[0070] A2. Determine the target environmental parameters of the dish by using the sensor;

[0071] A3, determining the target adjustment parameter corresponding to the target environmental parameter;

[0072] A4. Adjust the reference control parameter according to the target adjustment parameter to obtain the target control parameter;

[0073] A5. Control the dish protection device to work according to the target control parameter to protect the taste of the dish.

[0074] In the embodiment of the present application, the food protection device may include at least one of the following: a heating device (heat preservation device), a protective cover, a cooling device, a heat dissipation device, etc., which are not limited here.

[0075] Among them, the control parameters may include at least one of the following: heating time, heating temperature, heating frequency, cooling time, cooling temperature, cooling frequency, coverage area of ​​the protective cover, coverage time of the protective cover, heat dissipation time, etc., which are not limited here.

[0076] The target environment parameter may include at least one of the following: temperature, humidity, ambient light brightness, etc., which are not limited here. In a specific implementation, the target environment parameter may be obtained through a sensor. The sensor may include at least one of the following: a temperature sensor, a humidity sensor, an ambient light sensor, etc., which are not limited here.

[0077] In a specific implementation, a mapping relationship between preset dish names and control parameters of a dish protection device can be pre-stored, and reference control parameters of the dish protection device corresponding to the target dish name can be obtained based on the mapping relationship. Furthermore, the target environmental parameters of the dish can be determined by sensors. A mapping relationship between preset environmental parameters and adjustment parameters can be pre-stored, and the value range of the adjustment parameters is -0.2 to 0.2. The target adjustment parameters corresponding to the target environmental parameters can be determined based on the mapping relationship, and the reference control parameters can be adjusted according to the target adjustment parameters to obtain the target control parameters, the target control parameters = (1 + target adjustment parameters) * reference control parameters, and the dish protection device can be controlled to work according to the target control parameters to protect the taste of the dish, thereby improving the user's dining experience.

[0078] Optionally, the target environment parameters include internal environment parameters and external environment parameters, the internal environment parameters include environment parameters inside the dish, and the external environment parameters include environment parameters outside the dish; the above step 102, photographing the dish by the camera to obtain a dish image, may include the following steps:

[0079] 21. Photograph the dish with the camera to obtain an initial image;

[0080] 22. Perform target segmentation on the initial image to obtain a target area image;

[0081] 23. Determine a target image enhancement algorithm corresponding to the internal environment parameters;

[0082] 24. Obtaining initial algorithm control parameters corresponding to the target image enhancement algorithm;

[0083] 25. Determine a target deviation between the internal environmental parameter and the external environmental parameter;

[0084] 26. Determine a target optimization parameter corresponding to the target deviation;

[0085] 27. Optimizing the initial algorithm control parameters according to the target optimization parameters to obtain target algorithm control parameters;

[0086] 28. Photograph the dish according to the target algorithm control parameters and the target image enhancement algorithm to obtain the dish image.

[0087] Among them, the target environmental parameters include internal environmental parameters and external environmental parameters. The internal environmental parameters include environmental parameters inside the dish, and the external environmental parameters include environmental parameters outside the dish. In a specific implementation, a sensor can be set in the plate to obtain the internal environmental parameters inside the dish. A sensor can also be set on the tray rack to obtain the external environmental parameters within a preset range of the plate. The preset range can be pre-set or system default. The external environmental parameters can include at least one of the following: temperature, humidity, ambient light brightness, etc., which are not limited here. The internal environmental parameters can include at least one of the following: temperature, humidity, ambient light brightness, etc., which are not limited here.

[0088] Among them, the image enhancement algorithm may include at least one of the following: histogram equalization, sharpening, wavelet transform, neural network algorithm, etc., which are not limited here. Different image enhancement algorithms may correspond to different algorithm control parameters, and the algorithm control parameters are used to adjust the enhancement effect, calculation speed, image enhancement position, etc. of the image enhancement algorithm, which are not limited here.

[0089] In an embodiment of the present application, the dish can be photographed by a camera to obtain an initial image, and then the initial image can be segmented to obtain a target area image. The mapping relationship between preset environmental parameters and the image enhancement algorithm can also be pre-stored, and the target image enhancement algorithm corresponding to the internal environmental parameters can be determined based on the mapping relationship. The initial algorithm control parameters corresponding to the target image enhancement algorithm can also be obtained.

[0090] Furthermore, the target deviation between the internal environmental parameters and the external environmental parameters can be determined, the target deviation = [internal environmental parameters - external environmental parameters] / (external environmental parameters + internal environmental parameters), and then, the mapping relationship between the preset deviation and the optimization parameter can be pre-stored, and the target optimization parameter corresponding to the target deviation can be determined based on the mapping relationship. The value range of the optimization parameter can be -0.1 to 0.1. Then, part or all of the algorithm control parameters of the initial algorithm control parameters can be optimized according to the target optimization parameters to obtain the target algorithm control parameters, the target algorithm control parameters = (1 + target optimization parameters) * initial algorithm control parameters. Finally, the dish can be photographed according to the target algorithm control parameters and the target image enhancement algorithm to obtain the dish image. First, the image of the dish area can be captured. Second, the environmental parameters inside the dish can be obtained to determine the corresponding image enhancement algorithm. Third, the algorithm control parameters of the image enhancement algorithm can be dynamically adjusted based on the difference between the inside and outside of the dish, so that the depth of the image enhancement effect conforms to the actual environment, which helps to improve the accuracy of dish recognition and helps to improve the food delivery efficiency and accuracy of the food delivery robot.

[0091] It can be seen that the robot control method described in the embodiment of the present application is applied to a food delivery robot. The food delivery robot includes a tray rack and a camera. It detects whether there are dishes on the tray rack. When there are dishes on the tray rack, the dish is photographed by the camera to obtain a dish image, and the target dish name and target attribute information corresponding to the dish image are determined. The target attribute information includes at least one of the following: portion, plating method, color, and quantity. The dining table number corresponding to the target dish name and the target attribute information is determined, and m dining table numbers are obtained, where m is a positive integer. The order time for the m dining table numbers is obtained, and the m order times are determined. The earliest order time in a single period of time, obtains the target table number corresponding to the earliest order time, obtains the destination location of the target table number, obtains the current location of the food delivery robot, generates a navigation route between the current location and the destination location, and controls the food delivery robot to deliver the dishes to the destination location along the navigation route. It can not only automatically identify the dishes, but also locate the earliest ordered table number based on the dish name and attribute information of the dishes, and then, generates a navigation route based on the current location of the food delivery robot and the destination location of the earliest ordered table number, and uses the navigation route to complete the food delivery. In this way, the food delivery efficiency and accuracy of the food delivery robot can be improved.

[0092] See also Figure 2 , Figure 2 1 is a flow chart of a robot control method provided in an embodiment of the present application. As shown in the figure, the robot control method is applied to a food delivery robot. The food delivery robot includes a tray rack and a camera. The robot control method includes:

[0093] 201. Detect whether there are dishes on the tray rack.

[0094] 202. When there are dishes on the tray rack, the dishes are photographed by the camera to obtain dish images.

[0095] 203. Determine a target dish name and target attribute information corresponding to the dish image, wherein the target attribute information includes at least one of the following: portion, plating method, color, and quantity.

[0096] 204. Determine the dining table number corresponding to the target dish name and the target attribute information, and obtain m dining table numbers, where m is a positive integer.

[0097] 205. Obtain order times corresponding to the m dining table numbers to obtain m order times.

[0098] 206. Determine the earliest order time among the m order times, and obtain a target dining table number corresponding to the earliest order time.

[0099] 207. Obtain the destination location of the target dining table number and obtain the current location of the food delivery robot.

[0100] 208. Generate a navigation route between the current location and the destination location.

[0101] 209. When it is detected that an obstacle exists on the navigation route, modify the navigation route to bypass the obstacle and obtain a target navigation route.

[0102] 210. Control the food delivery robot to deliver the food to the destination location along the target navigation route.

[0103] Among them, obstacles may include at least one of the following: people, animals, other food delivery robots, warning lines, etc., which are not limited here.

[0104] The specific description of the above steps 201 to 210 can refer to the above Figure 1 The corresponding steps of the described robot control method will not be repeated here.

[0105] It can be seen that the robot control method described in the embodiment of the present application is applied to a food delivery robot, which includes a tray rack and a camera. The robot detects whether there are dishes on the tray rack. When there are dishes on the tray rack, the camera is used to photograph the dishes to obtain a dish image, and the target dish name and target attribute information corresponding to the dish image are determined. The target attribute information includes at least one of the following: portion, plating method, color, and quantity. The dining table number corresponding to the target dish name and the target attribute information is determined to obtain m dining table numbers, where m is a positive integer. The order times for the m dining table numbers are obtained to obtain the m order times. The earliest order time among the m order times is determined to obtain the target dining table number corresponding to the earliest order time. Take the destination position of the target table number, obtain the current position of the food delivery robot, generate a navigation route between the current position and the destination position, and when it is detected that there is an obstacle on the navigation route, modify the navigation route to bypass the obstacle to obtain the target navigation route, and control the food delivery robot to deliver the dishes to the destination position along the target navigation route. Not only can the dishes be automatically identified, but also the table number that placed the order earliest can be located based on the dish name and attribute information of the dish. Furthermore, a navigation route is generated based on the current position of the food delivery robot and the destination position of the table number that placed the order earliest. The navigation route can also be modified based on the obstacle. Finally, the food delivery is completed using the navigation route. In this way, the food delivery efficiency and accuracy of the food delivery robot can be improved.

[0106] In accordance with the above embodiment, please refer to Figure 3 , Figure 3 : is a structural schematic diagram of a computer device provided in an embodiment of the present application. As shown in the figure, it is applied to a food delivery robot. The food delivery robot includes a tray rack and a camera. The computer device includes a processor, a memory, a communication interface, and one or more programs. The one or more programs are stored in the memory and are configured to be executed by the processor. In the embodiment of the present application, the program includes instructions for executing the following steps:

[0107] Detecting whether there are dishes on the tray rack;

[0108] When there are dishes on the tray rack, the dishes are photographed by the camera to obtain a dish image;

[0109] Determine a target dish name and target attribute information corresponding to the dish image, wherein the target attribute information includes at least one of the following: portion, plating method, color, and quantity;

[0110] Determine the dining table number corresponding to the target dish name and the target attribute information, and obtain m dining table numbers, where m is a positive integer;

[0111] Obtain the order time associated with the m dining table numbers to obtain m order times;

[0112] Determine the earliest order time among the m order times, and obtain the target dining table number corresponding to the earliest order time;

[0113] Obtain the destination location of the target dining table number and the current location of the food delivery robot;

[0114] generating a navigation route between the current location and the destination location;

[0115] The food delivery robot is controlled to deliver the food to the destination along the navigation route.

[0116] Optionally, the food delivery robot further includes a food protection device and a sensor, and the above program further includes instructions for executing the following steps:

[0117] Acquire reference control parameters of the dish protection device corresponding to the target dish name;

[0118] Determining target environmental parameters of the dish by means of the sensor;

[0119] Determining a target adjustment parameter corresponding to the target environmental parameter;

[0120] Adjust the reference control parameter according to the target adjustment parameter to obtain the target control parameter;

[0121] The dish protection device is controlled to work according to the target control parameter to protect the taste of the dish.

[0122] Optionally, the target environmental parameters include internal environmental parameters and external environmental parameters, the internal environmental parameters include environmental parameters inside the dish, and the external environmental parameters include environmental parameters outside the dish;

[0123] In terms of photographing the dish by the camera to obtain a dish image, the program includes instructions for executing the following steps:

[0124] The dish is photographed by the camera to obtain an initial image;

[0125] Performing target segmentation on the initial image to obtain a target area image;

[0126] Determining a target image enhancement algorithm corresponding to the internal environment parameters;

[0127] Acquire initial algorithm control parameters corresponding to the target image enhancement algorithm;

[0128] determining a target deviation between the internal environmental parameter and the external environmental parameter;

[0129] Determining a target optimization parameter corresponding to the target deviation;

[0130] Optimizing the initial algorithm control parameters according to the target optimization parameters to obtain target algorithm control parameters;

[0131] The dish is photographed according to the target algorithm control parameters and the target image enhancement algorithm to obtain the dish image.

[0132] Optionally, a weight sensor is provided below the tray rack. In terms of detecting whether there are dishes on the tray rack, the program includes instructions for executing the following steps:

[0133] Detecting the target weight of the objects placed on the pallet rack by the weight sensor;

[0134] When the target weight is greater than a preset weight, it is determined that dishes exist on the tray rack.

[0135] Optionally, in the aspect of determining the dining table number corresponding to the target dish name and the target attribute information to obtain m dining table numbers, the program includes instructions for executing the following steps:

[0136] Acquire order information from the order system, wherein the order information includes n order lists, each of which includes at least one ordered dish, each ordered dish corresponds to a dish name and attribute information, each order list corresponds to a dining table number, and n is a positive integer greater than or equal to m;

[0137] Matching the dish names and attribute information of the ordered dishes in the n order lists with the target dish name and the target attribute information to obtain k target ordered dishes, where k is a positive integer not less than m;

[0138] Obtain the dining table numbers corresponding to the k target ordered dishes to obtain the m dining table numbers.

[0139] It can be seen that the computer device described in the embodiment of the present application is applied to a food delivery robot, which includes a tray rack and a camera to detect whether there are dishes on the tray rack. When there are dishes on the tray rack, the dish is photographed by the camera to obtain a dish image, and the target dish name and target attribute information corresponding to the dish image are determined, and the target attribute information includes at least one of the following: portion, plating method, color, and quantity. The dining table number corresponding to the target dish name and the target attribute information is determined, and m dining table numbers are obtained, where m is a positive integer. The order time for the m dining table numbers is obtained, and the m order times are obtained. The m order times are determined. The earliest order time in the time, obtains the target table number corresponding to the earliest order time, obtains the destination location of the target table number, obtains the current location of the food delivery robot, generates a navigation route between the current location and the destination location, and controls the food delivery robot to deliver the dishes to the destination location along the navigation route. It can not only automatically identify the dishes, but also locate the earliest ordered table number based on the dish name and attribute information of the dishes, and then, generates a navigation route based on the current location of the food delivery robot and the destination location of the earliest ordered table number, and uses the navigation route to complete the food delivery. In this way, the food delivery efficiency and accuracy of the food delivery robot can be improved.

[0140] Figure 4 400 is a functional unit block diagram of a robot control device 400 involved in an embodiment of the present application. The robot control device 400 is applied to a food delivery robot, the food delivery robot includes a tray rack and a camera, and the robot control device 400 includes: a detection unit 401, a shooting unit 402, a determination unit 403, an acquisition unit 404, a generation unit 405 and a control unit 406, wherein:

[0141] The detection unit 401 is used to detect whether there are dishes on the tray rack;

[0142] The photographing unit 402 is used to photograph the dishes by the camera to obtain dish images when there are dishes on the tray rack;

[0143] The determining unit 403 is used to determine the target dish name and target attribute information corresponding to the dish image, wherein the target attribute information includes at least one of the following: portion, plating method, color, and quantity; determine the dining table number corresponding to the target dish name and the target attribute information, and obtain m dining table numbers, where m is a positive integer;

[0144] The acquisition unit 404 is used to acquire the order time associated with the m dining table numbers to obtain m order times;

[0145] The determining unit 403 is further configured to determine the earliest order time among the m order times, and obtain a target dining table number corresponding to the earliest order time;

[0146] The acquisition unit 404 is further used to acquire the destination position of the target dining table number and the current position of the food delivery robot;

[0147] The generating unit 405 is used to generate a navigation route between the current location and the destination location;

[0148] The control unit 406 is used to control the food delivery robot to deliver the food to the destination along the navigation route.

[0149] Optionally, the food delivery robot further includes a food protection device and a sensor, and the robot control device 400 is further specifically used for:

[0150] Acquire reference control parameters of the dish protection device corresponding to the target dish name;

[0151] Determining target environmental parameters of the dish by means of the sensor;

[0152] Determining a target adjustment parameter corresponding to the target environmental parameter;

[0153] Adjust the reference control parameter according to the target adjustment parameter to obtain the target control parameter;

[0154] The dish protection device is controlled to work according to the target control parameter to protect the taste of the dish.

[0155] Optionally, the target environmental parameters include internal environmental parameters and external environmental parameters, the internal environmental parameters include environmental parameters inside the dish, and the external environmental parameters include environmental parameters outside the dish;

[0156] In the aspect of photographing the dish by the camera to obtain the dish image, the photographing unit 402 is specifically used for:

[0157] The dish is photographed by the camera to obtain an initial image;

[0158] Performing target segmentation on the initial image to obtain a target area image;

[0159] Determining a target image enhancement algorithm corresponding to the internal environment parameters;

[0160] Acquire initial algorithm control parameters corresponding to the target image enhancement algorithm;

[0161] determining a target deviation between the internal environmental parameter and the external environmental parameter;

[0162] Determining a target optimization parameter corresponding to the target deviation;

[0163] Optimizing the initial algorithm control parameters according to the target optimization parameters to obtain target algorithm control parameters;

[0164] The dish is photographed according to the target algorithm control parameters and the target image enhancement algorithm to obtain the dish image.

[0165] Optionally, a weight sensor is provided below the tray rack. In terms of detecting whether there are dishes on the tray rack, the detection unit 401 is specifically used for:

[0166] Detecting the target weight of the objects placed on the pallet rack by the weight sensor;

[0167] When the target weight is greater than a preset weight, it is determined that dishes exist on the tray rack.

[0168] Optionally, in determining the dining table number corresponding to the target dish name and the target attribute information to obtain m dining table numbers, the determining unit 403 is specifically used to:

[0169] Acquire order information from the order system, wherein the order information includes n order lists, each of which includes at least one ordered dish, each ordered dish corresponds to a dish name and attribute information, each order list corresponds to a dining table number, and n is a positive integer greater than or equal to m;

[0170] Matching the dish names and attribute information of the ordered dishes in the n order lists with the target dish name and the target attribute information to obtain k target ordered dishes, where k is a positive integer not less than m;

[0171] Obtain the dining table numbers corresponding to the k target ordered dishes to obtain the m dining table numbers.

[0172] It can be seen that the robot control device described in the embodiment of the present application is applied to a food delivery robot. The food delivery robot includes a tray rack and a camera. It detects whether there are dishes on the tray rack. When there are dishes on the tray rack, the dish is photographed by the camera to obtain a dish image, and the target dish name and target attribute information corresponding to the dish image are determined. The target attribute information includes at least one of the following: portion, plating method, color, and quantity. The dining table number corresponding to the target dish name and the target attribute information is determined, and m dining table numbers are obtained, where m is a positive integer. The order time for the m dining table numbers is obtained, and the m order times are determined. The earliest order time in a single period of time, obtains the target table number corresponding to the earliest order time, obtains the destination location of the target table number, obtains the current location of the food delivery robot, generates a navigation route between the current location and the destination location, and controls the food delivery robot to deliver the dishes to the destination location along the navigation route. It can not only automatically identify the dishes, but also locate the earliest ordered table number based on the dish name and attribute information of the dishes, and then, generates a navigation route based on the current location of the food delivery robot and the destination location of the earliest ordered table number, and uses the navigation route to complete the food delivery. In this way, the food delivery efficiency and accuracy of the food delivery robot can be improved.

[0173] It can be understood that the functions of each program module of the robot control device of this embodiment can be specifically implemented according to the method in the above method embodiment, and its specific implementation process can refer to the relevant description of the above method embodiment, which will not be repeated here.

[0174] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments.

[0175] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any method described in the above method embodiment. The computer program product may be a software installation package.

[0176] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0177] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0178] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0179] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0180] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0181] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0182] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0183] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A robot control method, characterized in that: Applied to a food delivery robot, the food delivery robot comprises a tray rack and a camera, and the method comprises: Detecting whether there are dishes on the tray rack; When there are dishes on the tray rack, the dishes are photographed by the camera to obtain a dish image; Determine a target dish name and target attribute information corresponding to the dish image, wherein the target attribute information includes: portion, plating method, color, and quantity; Determine the dining table number corresponding to the target dish name and the target attribute information, and obtain m dining table numbers, where m is a positive integer; Obtain the order time associated with the m dining table numbers to obtain m order times; Determine the earliest order time among the m order times, and obtain the target dining table number corresponding to the earliest order time; Obtain the destination location of the target dining table number and the current location of the food delivery robot; generating a navigation route between the current location and the destination location; Controlling the food delivery robot to deliver the food to the destination along the navigation route; When an obstacle is detected on the navigation route, modify the navigation route to bypass the obstacle to obtain a target navigation route; Controlling the food delivery robot to deliver the food to the destination location along the target navigation route; Wherein, the food delivery robot further includes a food protection device and a sensor, and the method further includes: Acquire reference control parameters of the dish protection device corresponding to the target dish name; Determining target environmental parameters of the dish by means of the sensor; Determining a target adjustment parameter corresponding to the target environmental parameter; Adjust the reference control parameter according to the target adjustment parameter to obtain the target control parameter; Controlling the dish protection device to work according to the target control parameter to protect the taste of the dish; Wherein, the target environment parameters include internal environment parameters and external environment parameters, the internal environment parameters include environment parameters inside the dish, and the external environment parameters include environment parameters outside the dish; The step of photographing the dish by the camera to obtain a dish image includes: The dish is photographed by the camera to obtain an initial image; Performing target segmentation on the initial image to obtain a target area image; Determining a target image enhancement algorithm corresponding to the internal environment parameters; Acquire initial algorithm control parameters corresponding to the target image enhancement algorithm; determining a target deviation between the internal environmental parameter and the external environmental parameter; Determining a target optimization parameter corresponding to the target deviation; Optimizing the initial algorithm control parameters according to the target optimization parameters to obtain target algorithm control parameters; The dish is photographed according to the target algorithm control parameters and the target image enhancement algorithm to obtain the dish image.

2. The method according to claim 1, characterized in that: A weight sensor is provided below the tray rack, and the detection of whether there is food on the tray rack includes: Detecting the target weight of the objects placed on the pallet rack by the weight sensor; When the target weight is greater than a preset weight, it is determined that dishes exist on the tray rack.

3. The method according to claim 1, characterized in that: The determining of the dining table number corresponding to the target dish name and the target attribute information to obtain m dining table numbers includes: Acquire order information from the order system, wherein the order information includes n order lists, each of which includes at least one ordered dish, each ordered dish corresponds to a dish name and attribute information, each order list corresponds to a dining table number, and n is a positive integer greater than or equal to m; Matching the dish names and attribute information of the ordered dishes in the n order lists with the target dish name and the target attribute information to obtain k target ordered dishes, where k is a positive integer not less than m; Obtain the dining table numbers corresponding to the k target ordered dishes to obtain the m dining table numbers.

4. A robot control device, characterized in that: Applied to a food delivery robot, the food delivery robot includes a tray rack and a camera, the device includes: a detection unit, a shooting unit, a determination unit, an acquisition unit, a generation unit and a control unit, wherein: The detection unit is used to detect whether there are dishes on the tray rack; The photographing unit is used to photograph the dishes through the camera to obtain dish images when there are dishes on the tray rack; The determining unit is used to determine the target dish name and target attribute information corresponding to the dish image, wherein the target attribute information includes: portion, plating method, color, and quantity; determine the dining table number corresponding to the target dish name and the target attribute information, and obtain m dining table numbers, where m is a positive integer; The acquisition unit is used to acquire the order time associated with the m dining table numbers to obtain m order times; The determining unit is further configured to determine the earliest order time among the m order times, and obtain a target dining table number corresponding to the earliest order time; The acquisition unit is further used to acquire the destination position of the target dining table number and the current position of the food delivery robot; The generating unit is used to generate a navigation route between the current location and the destination location; The control unit is used to control the food delivery robot to deliver the food to the destination along the navigation route; The device is also specifically used for: When an obstacle is detected on the navigation route, modify the navigation route to bypass the obstacle to obtain a target navigation route; Controlling the food delivery robot to deliver the food to the destination location along the target navigation route; The food delivery robot further includes a food protection device and a sensor, and the device is also specifically used for: Acquire reference control parameters of the dish protection device corresponding to the target dish name; Determining target environmental parameters of the dish by means of the sensor; Determining a target adjustment parameter corresponding to the target environmental parameter; Adjust the reference control parameter according to the target adjustment parameter to obtain the target control parameter; Controlling the dish protection device to work according to the target control parameter to protect the taste of the dish; Wherein, the target environment parameters include internal environment parameters and external environment parameters, the internal environment parameters include environment parameters inside the dish, and the external environment parameters include environment parameters outside the dish; In the aspect of photographing the dish by the camera to obtain the dish image, the photographing unit is specifically used for: The dish is photographed by the camera to obtain an initial image; Performing target segmentation on the initial image to obtain a target area image; Determining a target image enhancement algorithm corresponding to the internal environment parameters; Acquire initial algorithm control parameters corresponding to the target image enhancement algorithm; determining a target deviation between the internal environmental parameter and the external environmental parameter; Determining a target optimization parameter corresponding to the target deviation; Optimizing the initial algorithm control parameters according to the target optimization parameters to obtain target algorithm control parameters; The dish is photographed according to the target algorithm control parameters and the target image enhancement algorithm to obtain the dish image.

5. A computer device, characterized in that: The method comprises a processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, wherein the program comprises instructions for executing the steps in the method according to any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: A computer program for electronic data exchange is stored, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 3.

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