A control method and control device of a delivery robot, and a delivery system

Abstract

The application provides a control method and device of a delivery robot and a delivery system. The control method is applied to a cloud platform and includes the following steps: determining a target delivery robot and an expected working mode of the target delivery robot according to running parameters of each delivery robot in a delivery environment and delivery task parameters; controlling the target delivery robot to switch from a current working mode to the expected working mode; and controlling the switching state of different components in the delivery robot in different working modes, so that the delivery robot executes power saving strategies with different power saving degrees. In this way, the problems of a small number of tasks that can be executed by a robot per day, low use efficiency and the inability to meet user needs in a timely manner in the prior art can be solved, the power of the delivery robot is accurately utilized, the endurance time of the robot is prolonged, and the use efficiency of the robot is improved.

Description

Technical Field

[0001] This application relates to the field of robotics technology, and in particular to a control method, control device and delivery system for a delivery robot. Background Technology

[0002] As robots become increasingly complex, their battery capacity is insufficient to support prolonged continuous operation, necessitating frequent pauses for charging. For delivery robots in scenarios like restaurants or hotels, their workload often dwindles after completing the midday peak delivery period, leaving them unable to remain operational until the evening peak. Therefore, to ensure smooth evening delivery operations, multiple charging cycles are required, resulting in a limited number of daily tasks and low efficiency. Conversely, without recharging, delivery robots cannot complete their tasks at night, failing to meet timely customer needs. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a control method, control device and delivery system for a delivery robot, which can solve the problems of the limited number of tasks that the robot can perform per day, low utilization efficiency and inability to meet user needs in a timely manner in the prior art, so as to achieve the purpose of accurately utilizing the power of the delivery robot, extending the robot's battery life and thus improving the robot's utilization efficiency.

[0004] This application provides a control method for a delivery robot, wherein the delivery robot, when performing a delivery task, transports items from a pickup point to a delivery point; the control method is applied to a cloud platform and includes:

[0005] Based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment, a target delivery robot and its expected working mode are determined from among the delivery robots; wherein, the delivery task parameters include at least one of the following: the production progress of the delivery items, the execution status of the delivery task, and the number of delivery tasks;

[0006] The target delivery robot is controlled to switch from the current working mode to the desired working mode; in different working modes, the delivery robot executes different power-saving strategies by controlling the switching states of different components in the delivery robot.

[0007] This application embodiment also provides a control device for a delivery robot, which, when performing a delivery task, transports items from a pickup point to a delivery point; the control device is applied to a cloud platform and includes:

[0008] The determination module is used to determine the target delivery robot and its expected working mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment; wherein, the delivery task parameters include at least one of the following: the production progress of the delivery items, the execution status of the delivery task, and the number of delivery tasks.

[0009] The control module is used to control the target delivery robot to switch from the current working mode to the desired working mode; in different working modes, the delivery robot executes power-saving strategies of different power-saving levels by controlling the switching states of different components in the delivery robot.

[0010] This application embodiment also provides a delivery system, the delivery system including a delivery robot and a cloud platform; the delivery robot and the cloud platform are communicatively connected.

[0011] The cloud platform is used to determine the target delivery robot and its desired working mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment; and to control the target delivery robot to switch from the current working mode to the desired working mode; wherein, the delivery task parameters include at least one of the following: the production progress of the delivered items, the execution status of the delivery task, and the number of delivery tasks; and in different working modes, the delivery robot executes power-saving strategies with different levels of power saving by controlling the on / off states of different components in the delivery robot;

[0012] The delivery robot is used to switch from the current working mode to the desired working mode under the control of the cloud platform.

[0013] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the control method for a delivery robot described above.

[0014] The embodiments of this application have the following beneficial technical effects:

[0015] This application provides a control method, control device, and delivery system for a delivery robot. The system automatically switches the working mode according to the robot's operating parameters and delivery task parameters to control the on / off state of different components in the robot. While ensuring that the robot can complete the delivery task, it can also reduce the power consumption of unnecessary components, achieve precise power utilization, extend the battery life, and thus improve the robot's efficiency.

[0016] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart of a control method for a delivery robot provided in an embodiment of this application is shown;

[0019] Figure 2 This illustration shows one of the structural schematic diagrams of a control device for a delivery robot provided in an embodiment of this application;

[0020] Figure 3 This is a second schematic diagram of the structure of a control device for a delivery robot provided in an embodiment of this application;

[0021] Figure 4 A schematic diagram of the structure of a delivery system provided in an embodiment of this application is shown. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. Based on the embodiments of this application, every other embodiment obtained by those skilled in the art without inventive effort falls within the scope of protection of this application.

[0023] First, the applicable application scenarios of this application will be introduced. This application is applied to the field of robotics. Specifically, the delivery robot in the embodiments of this application is a delivery robot used to transport items to delivery points when performing delivery tasks. As an intelligent device that replaces manual delivery services, it not only brings customers a novel experience but also reduces the intensity of manual labor and improves work efficiency. It has been increasingly used in canteens, restaurants, hotels, and other places.

[0024] In one embodiment, the delivery robot performs the following steps during the delivery process:

[0025] Step 101: The delivery robot moves to the target delivery point.

[0026] Delivery robots can perform delivery tasks, delivering items to users, such as room delivery in hotels or food preparation in restaurants. Delivery tasks can be services that deliver goods to users. Delivery scenarios include residential communities, warehouses, airports, hotels, and restaurants. The delivery point refers to a pre-designated location or area within the delivery scenario. The delivery robot can move to the delivery point, notify the user, and wait for the user to pick up the item. For example, the delivery point can be a specific location within the delivery scenario, such as a building in a residential community, the door of a room in a hotel, or next to a table in a restaurant. The target delivery point is the specific address to which the target delivery task requires delivery. For example, if the target delivery task is to provide express delivery service to room B in area A, the robot can move to the target delivery point, which is the door of room B in area A, and call the landline inside the room to notify the user to pick up the package. Similarly, if the target delivery task is to provide food delivery service to door D in hotel C, the robot can move to the target delivery point, which is door D in hotel C, and call the phone inside the door to notify the user to pick up the food. Or, if the target delivery task is to provide food delivery service to table F in restaurant E, the robot can move to the target delivery point, which is table F in restaurant E, and control the bell on table F to notify the user to pick up the food.

[0027] In a specific example, the delivery scenario is a hotel, and the delivery robots can be hotel delivery robots. Each delivery robot has an identification information, such as an ID (Identity Document), to identify its identity. The delivery points for the hotel's delivery robots include the area in front of the hotel rooms. After checking into the hotel, users can order food or daily necessities through the hotel's ordering system. This ordering system can be a telephone order or a mobile app service system. For example, when ordering food, users can reserve meals through the ordering system and enter their room number. The ordering system sends the user's reservation information to the hotel's platform system. The platform system can then generate a target delivery task based on the user's room number and reservation information and send it to the hotel's delivery robots. After obtaining the reservation from hotel staff, the robot moves to the target delivery point, which can be the area in front of the user's room.

[0028] In another concrete example, the delivery scenario is a restaurant, and the delivery robot can be the restaurant's own delivery robot. The delivery points for this restaurant's delivery robot include dining areas within the restaurant, such as the area where the user is located. After selecting a table, the user can place an order using the corresponding ordering system, such as scanning a QR code on the table. The user can manually enter the table number or have it automatically entered. The ordering system sends the user's reservation information to the restaurant's platform system. The platform system then uses the user's table number and reservation information to generate a target delivery task, which is sent to the delivery robot within the restaurant. After obtaining the reservation from restaurant staff, the robot moves to the target delivery point, which can be the user's table area. This autonomous delivery by delivery robots significantly reduces labor costs and improves service quality.

[0029] Step 102: The delivery robot triggers key generation. The key is used to confirm pickup, such as a pickup code.

[0030] Step 103: The delivery robot notifies the user at the target delivery point to pick up the item via communication connection.

[0031] The delivery robot can transmit voice messages to users via a communication connection, prompting them to move to the target delivery point to pick up their items. Users receive these prompts from the robot. The delivery robot can also inform users of the delivered item information and the location of the target delivery point via voice. After confirming that the item being delivered is the one they ordered, the user proceeds to the target delivery point to retrieve it.

[0032] For example, when the delivery robot arrives at the user's dining location, it can call the phone on the table to remind the user to pick up the food. After the user confirms that the food delivered by the robot is the food they ordered, they can pick up the food delivered by the robot.

[0033] The delivery robot provided in this application includes a shelf inside its housing. The shelf is fixed to the mobile chassis of the delivery robot and has multiple storage layers. Each storage layer can hold delivery items. By setting up a shelf with multiple storage layers, the delivery robot can store multiple items, enabling it to deliver multiple items in one operation, thereby improving the delivery efficiency of the delivery robot.

[0034] Furthermore, the delivery robot provided in this application embodiment also includes a delivery item detection sensor, an obstacle detection sensor, a visual interaction component, and a motion component. The obstacle detection sensor may be located on the bottom of the robot to detect whether there are obstacles in the robot's movement path; the motion component refers to an electric component that can drive the robot to move autonomously; the visual interaction component refers to a component that can visually interact with the user, such as a charging indicator light, ambient light, and a display screen. More specifically, the display screen includes an information display screen and an operation interaction screen. The information display screen may be a large screen located on the robot body, generally used to display promotional information; the operation interaction screen may be a touchscreen installed on the robot's head, generally used for operation interaction with the user, such as receiving user operation commands and providing feedback to the user.

[0035] Furthermore, when using a delivery robot to deliver items, you need to first place the items to be delivered in the storage layer set in the robot, and then select the delivery location corresponding to the storage layer. Here, each storage layer needs to select its corresponding delivery location. After selecting the delivery location corresponding to each storage layer, click the "Start Now" button on the delivery robot, and the delivery robot can directly enter the delivery page and execute the delivery task.

[0036] However, research has found that as robots become increasingly complex, their battery capacity is insufficient to support prolonged continuous operation, necessitating frequent pauses for charging. For delivery robots, particularly in restaurant or hotel delivery scenarios, their workload often dwindles after completing the midday peak, leaving them unable to remain operational until the evening peak. Therefore, to ensure smooth evening delivery operations, multiple charging cycles are required, resulting in a limited number of daily tasks and low efficiency. Without these additional charging cycles, delivery robots cannot complete their tasks at night, failing to meet timely customer needs.

[0037] Based on this, the present application provides a control method for a delivery robot, which can solve the problems of the limited number of tasks that the robot can perform each day, low utilization efficiency, and inability to meet user needs in a timely manner in the prior art. It can achieve the goal of accurately utilizing the delivery robot's power, extending the robot's battery life, and thus improving the robot's utilization efficiency.

[0038] The control method for delivery robots provided in this application is applied to a cloud platform; the cloud platform is connected to each delivery robot in the delivery environment; the delivery environment refers to the physical space where the delivery robots are located, and at least one delivery robot is distributed in the delivery environment; the cloud platform can obtain data parameters sent by each delivery robot in the delivery environment and issue control commands to each delivery robot based on the communication connection.

[0039] Please see Figure 1 , Figure 1 This is a flowchart illustrating a control method for a delivery robot provided in an embodiment of this application. Figure 1 As shown in the embodiments of this application, the control method includes:

[0040] S201. Based on the operating parameters of each delivery robot in the delivery environment and the delivery task parameters, determine the target delivery robot and the desired working mode of the target delivery robot from among the delivery robots.

[0041] The operating parameters of the delivery robot include at least one of the following: the robot's real-time location, real-time battery level, and delivery item placement signal. The delivery robot can collect these operating parameters through various onboard hardware devices and send them to the cloud platform. For example, the delivery robot can collect its real-time location through its own positioning device, its real-time battery level through its battery management system, and the delivery item placement signal through delivery item detection sensors. These delivery item detection sensors can be weight sensors that detect the weight of the items carried by the robot, or tag detection sensors that identify tags attached to the delivery items.

[0042] The delivery task parameters include at least one of the following: the production progress of the delivery items, the execution status of the delivery task, and the number of delivery tasks.

[0043] Taking a restaurant scenario as an example, the cloud platform can determine the preparation progress of delivered items in real time by linking with the restaurant's backend menu system. For instance, when a user places an order through the ordering system corresponding to their table, the backend menu system receives the item information and initializes the preparation progress to "not being prepared." When the chef begins preparing the item according to the information, the backend menu system is triggered to set the preparation progress to "being prepared." Then, based on a pre-set preparation time, the backend menu system estimates the expected completion time of the item. If the time difference between the estimated completion time and the current time is less than a preset time difference, the preparation progress is set to "almost completed." When the item is actually completed, the chef can trigger the backend menu system to set the preparation progress to "completed." Here, the backend menu system can be integrated into the cloud platform or communicate with it to continuously update the preparation progress, allowing the cloud platform to obtain the real-time preparation progress of each ordered item.

[0044] Regarding the execution status of delivery tasks, after a user places an order using the ordering system corresponding to the table, the ordering system or the back-end menu system can generate a delivery task, set the execution status of the delivery task to "pending execution," and synchronize the generated delivery task and its execution status to the cloud platform. Then, once the delivery item for any pending delivery task is prepared, the delivery robot receiving the task can set the execution status of the delivery task to "in execution" after detecting the placement signal of the delivery item through the delivery item detection sensor, or after receiving a trigger operation from a service personnel or an execution command. Subsequently, the delivery robot executes the delivery task, transporting the delivery item from the pickup point to the delivery point. After the delivery robot detects that the user has correctly taken the delivery item at the delivery point, it can set the execution status of the delivery task to "completed." Here, the cloud platform, through its communication connection with each delivery robot, can obtain and update the execution status of the delivery tasks executed by each delivery robot in real time.

[0045] The number of delivery tasks includes both the number of tasks that have been sent to delivery robots and are currently being executed, and the number of delivery tasks that are yet to be executed and have not yet been assigned to delivery robots.

[0046] In this step, the cloud platform accurately determines the working status of each delivery robot based on the diverse operating parameters and delivery task parameters described above. This allows it to identify the target delivery robot that needs to switch operating modes, and the desired operating mode that the target robot should switch to, which aligns with its current working status. In different operating modes, the on / off states of different components within the delivery robot vary. This ensures the robot can complete its delivery tasks while reducing unnecessary power consumption by shutting down unnecessary components.

[0047] S202, Control the target delivery robot to switch from the current working mode to the desired working mode.

[0048] In different working modes, by controlling the switching states of different components in the delivery robot, the delivery robot can implement power-saving strategies with different levels of power saving.

[0049] In this step, the cloud platform can send a control command to the target delivery robot to switch to the desired operating mode. The target delivery robot responds to the received control command and switches from its current operating mode to the desired operating mode. In specific implementation, the controller on the target delivery robot determines the power-saving strategy corresponding to the desired operating mode according to a pre-configured mapping relationship between operating modes and power-saving strategies. The power-saving strategy specifies the on / off states of different components in the delivery robot; different power-saving strategies have different levels of power saving, and the on / off states of each component are not entirely the same. The controller can control the on / off states of different components according to the power-saving strategy, achieving the goal of activating necessary components to complete the delivery task while shutting down unnecessary components to save energy.

[0050] The following example, using a restaurant as the delivery scenario and a restaurant food delivery task as the delivery task, will detail how the control method provided in this application embodiment determines the target delivery robot and the desired working mode of the target delivery robot at each stage of the delivery task.

[0051] In this example, the pickup point could be the restaurant's food preparation area. Delivery robots would queue up within a preset area around the food preparation area, forming a waiting queue. The robots would then move sequentially to the food preparation area to await delivery. Afterward, they would transport the items to the customer's table, i.e., the delivery point. The restaurant could have one or more food preparation areas. When there were multiple areas, priorities could be set between them. For example, the area closest to the kitchen would have the highest priority, and the delivery robot would move to that area first to perform the delivery task.

[0052] In a first possible implementation, while waiting for the delivery item to be completed, the delivery robot forms a waiting queue within a preset range of the pickup point; when the operating parameters include the real-time position of the delivery robot and the delivery item placement signal, and the delivery task parameters include the production progress of the delivery item; step S201 may include:

[0053] Step A1: When the production progress indicator of the delivery item shows that there is a target delivery item, the first delivery robot in the waiting queue located within the preset range of the pickup point is identified as the target delivery robot based on the real-time location of each delivery robot.

[0054] The target delivery item is defined as an item for which the time difference between the estimated completion time and the current time is less than a preset time difference. The preset time difference can be set comprehensively based on factors such as the distance between the waiting queue and the pickup point, and can be adaptively adjusted based on factors such as the number of tasks being performed by the delivery robot and the number of delivery robots in the waiting queue, such as 2 minutes or 3 minutes, etc. This application does not impose any limitations on it.

[0055] Here, the delivery robots in the waiting queue are in standby mode. In standby mode, the delivery robot's item detection sensors, obstacle detection sensors, visual interaction components, and motion components are all turned off. In this way, the delivery robots in the waiting queue can conserve energy by remaining in standby mode while waiting for the items to be prepared, when they have no delivery tasks.

[0056] Therefore, in this step, when the production progress indicator of the delivery item shows that there is a target delivery item, it means that a delivery item is about to be completed and needs to be delivered by the delivery robot; at this time, based on the real-time position of each delivery robot, the first delivery robot in the waiting queue is identified as the target delivery robot.

[0057] Step A2: Determine that the desired working mode of the target delivery robot is wake-up mode.

[0058] Here, in wake-up mode, the delivery robot's item detection sensors, obstacle detection sensors, and motion components are activated, while the visual interaction components are deactivated. Therefore, in wake-up mode, the delivery robot possesses obstacle detection and motion capabilities, and can move to the target location according to motion commands.

[0059] Afterwards, the cloud platform can issue a movement command to the target delivery robot to move to the pickup point, or the controller on the target delivery robot can also generate a movement command to move to the pickup point according to the pre-set control program, both of which can control the target delivery robot to move to the pickup point.

[0060] Step A3: When the real-time location of the current target delivery robot is detected to have reached the pickup point, and the delivery item placement signal is received from the delivery item detection sensor of the target delivery robot, the desired working mode of the target delivery robot is determined to be the full working mode.

[0061] In this step, when the cloud platform detects that the real-time location of the currently determined target delivery robot has reached the pickup point and receives the delivery item placement signal detected by the delivery item detection sensor, it indicates that a delivery item has been placed into the target delivery robot at the pickup point. At this time, the desired working mode is determined to be the full working mode.

[0062] In full operating mode, its delivery item detection sensors, obstacle detection sensors, visual interaction components, and motion components are all activated. At this time, the delivery robot can depart at any time to perform delivery tasks, autonomously moving to the delivery point indicated by the task. Thus, once a delivery item placement signal is detected, the delivery robot switches to full motion mode, ensuring timely execution of delivery tasks and improving delivery efficiency.

[0063] It should be noted that when the target delivery robot reaches the pickup point in real time and receives the delivery item placement signal, the target delivery robot can immediately set off to execute the delivery task. Alternatively, the target delivery robot can compare the delivery items indicated by the received delivery task with the delivery items indicated by the delivery item placement signal. When it determines that all delivery items indicated by the delivery task have been placed, or detects that all the storage layers of the target delivery robot are full, or receives a delivery task execution command triggered by relevant personnel through the operation interface, it will immediately set off to execute the delivery task.

[0064] In another example, after step A1, step S201 may also include:

[0065] A4. When it is determined that the quantity of the target delivery items is greater than the quantity of items that the current target delivery robot can carry, the number of additional delivery robots required is predicted based on the quantity of the target delivery items.

[0066] Here, each delivery robot has limited carrying space and a limited number of items it can carry. During peak delivery periods, the number of target items may exceed the capacity of the first target delivery robot. In this case, the number of additional delivery robots needed can be predicted based on the number of target items and the capacity of each robot.

[0067] A5. Based on the number of delivery robots still needed, determine the remaining number of other delivery robots in the waiting queue as the target delivery robots in sequence, and determine the expected working mode of the other delivery robots as the wake-up mode in sequence.

[0068] In this step, based on the number of remaining delivery robots, the other delivery robots still needed in the waiting queue are sequentially identified as target delivery robots, and their expected operating modes are sequentially set to wake-up modes. Then, the cloud platform can sequentially issue movement commands to the target delivery robots to move to the pickup point, or the controllers on each target delivery robot can generate movement commands according to pre-set control programs to control the target delivery robots to move sequentially to the pickup point. In this way, by predicting the number of remaining delivery robots and sequentially waking them up, during peak delivery periods when a large number of items are about to be completed, the waiting time for completed items to be delivered can be reduced, improving delivery efficiency.

[0069] It should be noted that after determining the desired working mode of the other delivery robots to the wake-up mode in step A5, the desired working mode of the other delivery robots can be determined to the full working mode in the same way as in step A3, so that the other delivery robots can start to perform delivery tasks. The specific method can be referred to the description in step A3, and the same technical effect can be achieved.

[0070] In another example, when the operating parameters also include the execution status of the delivery task, step S201 may further include:

[0071] A6. When it is detected that the real-time location of the current target delivery robot has left the pickup point and the delivery task is in execution status, the other delivery robots in the waiting queue are sequentially identified as the target delivery robot, and the expected working mode of the other delivery robots is sequentially identified as the wake-up mode.

[0072] In this step, when it is detected that the current target delivery robot has left the pickup point and the delivery task is in progress, it indicates that the current target delivery robot has started to execute the delivery task. In order to ensure that the remaining delivery robots in the waiting queue can move to the pickup point more quickly later, the other delivery robots in the waiting queue are identified as target delivery robots in turn, and their expected working mode is identified as wake-up mode in turn.

[0073] Afterwards, the cloud platform or the controller on the target delivery robot can generate a movement command to move forward to the original position of the previous delivery robot in the waiting queue. This allows the remaining delivery robots in the waiting queue to move forward in sequence according to the order of the waiting queue. In this way, when a new target delivery item is generated, the first delivery robot in the waiting queue will be closer to the pickup point and can pick up the delivery item more quickly for delivery.

[0074] Here, the real-time location of the delivery robot and the execution status of the delivery task are combined to determine whether the target delivery robot has started to perform the delivery task. This is to avoid misjudging a situation where the delivery robot has left the pickup point but has not performed the delivery task as if the robot has started to perform the delivery task, such as when the robot being delivered is manually moved or taken to a charging station. If a delivery robot has left the pickup point but has not performed the delivery task, the first delivery robot in the remaining waiting queue can be identified as the target delivery robot and controlled in the manner described in steps A2-A3.

[0075] A7. When it is detected that other delivery robots in the wake-up mode have moved sequentially to the original position of the previous delivery robot in the waiting queue, if the production progress indicator of the delivery item does not contain the target delivery item, the expected working mode of the other delivery robots is redefined as the standby mode.

[0076] In this step, when it is detected that other delivery robots in the wake-up mode have moved to the original position of the previous delivery robot in the waiting queue, it means that the remaining delivery robots in the waiting queue have moved forward in the order of the waiting queue, and the positions of the delivery robots in the waiting queue have been rearranged.

[0077] If the production progress indicator for the delivery item does not show a target delivery item, the expected operating mode of the other delivery robots is reset to standby mode. This allows the other delivery robots to re-enter standby mode and wait for the target delivery item to be generated before waking up, thus conserving power and extending the robot's battery life. If the production progress indicator shows a target delivery item, the first delivery robot in the waiting queue is designated as the target delivery robot. Its wake-up operating mode remains unchanged, and the target delivery robot moves to the pickup point to retrieve the item. The remaining delivery robots repeat steps A6 and A7.

[0078] In this way, the system can automatically control the wake-up and sleep times of delivery robots in the waiting queue based on the production progress of the delivered items. When a delivery item is about to be completed, the delivery robot in the waiting queue is woken up from standby mode, promptly arrives at the pickup point, and departs to perform the delivery task as soon as it receives the item. At the same time, other delivery robots in the waiting queue are woken up in turn to fill the gap and prepare to perform new delivery tasks. When there are no new delivery items, they return to standby mode. In this way, while ensuring efficient completion of delivery tasks, unnecessary power consumption is reduced, achieving precise utilization of the delivery robot's power, extending the robot's battery life, thereby reducing the number of charging cycles and improving the robot's utilization efficiency.

[0079] In a second possible implementation, once the target robot transports the delivery item to the delivery point and the item is correctly retrieved, the execution status of the delivery task switches from "in execution" to "completed." In this case, the operating parameters include the delivery robot's real-time battery level and real-time location, and the delivery task parameters include the execution status of the delivery task; step S201 may further include:

[0080] Step B1: When the execution status of any delivery robot's delivery task changes from "in execution" to "execution completed", the delivery robot is identified as the target delivery robot, and the desired working mode is set to "return mode".

[0081] Here, in return-to-home mode, the delivery robot's obstacle detection sensors, visual interaction components, and motion components are activated, while the delivery item detection sensors are deactivated. This is because after the delivery task is completed, the delivery robot no longer needs to check whether the delivery item has been correctly picked up, so the delivery item detection sensors can be turned off to save power.

[0082] Step B2: Determine whether the real-time battery level of the target delivery robot is lower than the first preset battery threshold.

[0083] Here, the first preset power threshold can be set and dynamically adjusted adaptively by comprehensively considering factors such as the battery capacity of the delivery robot, power consumption, the area of ​​the delivery environment, and the number of delivery tasks to be executed. For example, it can be set to 30%. This application does not impose any restrictions on this.

[0084] Step B3: If the battery level is below the first preset power threshold, control the target delivery robot to move to the charging point based on its real-time location.

[0085] Step B4: Once the real-time location of the target delivery robot is determined to have reached the charging point, the desired working mode is set to charging mode.

[0086] For steps B3 and B4, if it is determined that the real-time battery level of the target delivery robot is lower than the first preset battery threshold, it means that the target delivery robot is low on battery and needs to be charged. At this time, the target delivery robot can be controlled to move to the preset charging point in the delivery environment based on its real-time position. After the target delivery robot reaches the charging point, the desired working mode is set to the charging mode.

[0087] In charging mode, the charging indicator light in the delivery robot's visual interaction component is turned on, while the delivery item detection sensor, obstacle detection sensor, motion component, and other visual interaction components are all turned off. This reduces unnecessary power consumption, improves charging efficiency, and allows the delivery robot to be fully charged as soon as possible to perform delivery tasks, thereby improving the robot's utilization efficiency.

[0088] On the other hand, the delivery robot in charging mode will be woken up when it detects events such as the touch screen being clicked or buttons on the robot being pressed, in order to meet the user's needs. If no new events occur within a certain period after being woken up, the delivery robot will re-enter charging mode to conserve power.

[0089] Step B5: If the power level is not lower than the first preset power threshold, then control the target delivery robot to move to the end of the waiting queue based on the real-time position of the target delivery robot.

[0090] Step B6: Once the real-time location of the target delivery robot is determined to have reached the end of the waiting queue, the desired working mode is set to standby mode.

[0091] For steps B5 and B6, if it is determined that the real-time battery level of the target delivery robot is not lower than the first preset battery threshold, it means that the target delivery robot has sufficient battery power and does not need to be charged. At this time, the target delivery robot can be controlled to move to the end of the waiting queue according to its real-time position to wait for a new delivery task to be executed; and after it is determined that the target delivery robot has reached the end of the waiting queue, the desired working mode is set to standby mode.

[0092] In this way, based on the execution status of the delivery task, the real-time battery level and real-time location of the delivery robot, the robot can be automatically controlled to return to the waiting queue or return to charge after the delivery task is completed. In charging mode, turning off multiple components except for the charging indicator light can reduce unnecessary power consumption and improve the charging efficiency of the delivery robot.

[0093] In a third possible implementation, when the operating parameters include the real-time battery level of the delivery robot and the delivery task parameters include the number of delivery tasks, step S201 may further include:

[0094] Step C1: When the predicted number of delivery tasks increases, the delivery robot that is in the charging mode and has a real-time power level higher than the second preset power threshold is identified as the target delivery robot.

[0095] Here, when there are too many delivery tasks, there may be a relative shortage of available delivery robots in the waiting queue, resulting in the delivery items being completed but no available delivery robots to perform the delivery task, thus reducing delivery efficiency.

[0096] In this step, when the cloud platform predicts an increase in the number of delivery tasks, it can pre-select delivery robots that are charging at charging points and whose real-time battery level is higher than a second preset battery threshold as target delivery robots. Here, the second preset battery threshold can also be set and dynamically adjusted adaptively by comprehensively considering factors such as the delivery robot's battery capacity, power consumption, the area of ​​the delivery environment, and the predicted number of delivery tasks, for example, 70%. This application does not impose any limitations on this.

[0097] Step C2: Set the desired operating mode of the target delivery robot to wake-up mode to control the target delivery robot to move towards the pickup point.

[0098] In this step, the cloud platform determines the desired operating mode of the target delivery robot as wake-up mode, thereby waking the robot from charging mode and enabling it to move. Then, the cloud platform or the target delivery robot's controller can control the robot to move towards the pickup point. More specifically, the target delivery robot will move to the end of the waiting queue, waiting to pick up items in turn. Additionally, the cloud platform can also wake up each delivery robot in the waiting queue in advance, switching it from standby mode to wake-up mode.

[0099] In this way, when the cloud platform predicts an increase in the number of delivery tasks, it can wake up the delivery robots in charging mode in advance to prepare for delivery. This way, when new target delivery items are generated, they can be assigned to delivery robots for delivery more quickly, thereby improving delivery efficiency.

[0100] Furthermore, step S201 may also include:

[0101] Step C3: When it is determined that the number of delivery tasks is less than a preset quantity threshold or the number of delivery tasks is predicted to decrease, other delivery robots other than the first robot in the waiting queue within the preset range of the pickup point are identified as the target delivery robots.

[0102] Step C4: Determine the desired working mode of the target delivery robot as standby mode.

[0103] Regarding steps C3 and C4, when the number of delivery tasks is less than a preset threshold or when it is predicted that the number of delivery tasks will soon fall below the preset threshold, there may be a relative surplus of available delivery robots in the waiting queue. Therefore, delivery robots other than the first robot in the waiting queue can be identified as target delivery robots to control them into standby mode, thus conserving power. Here, the preset threshold can also be set and dynamically adjusted adaptively by comprehensively considering factors such as the number of delivery robots and the area of ​​the delivery environment; this application does not impose any limitations on it.

[0104] In practical implementation, the number of delivery tasks can be predicted in the following ways:

[0105] The system receives customer flow data sent by a robot performing a greeting task; wherein the customer flow data is determined by the robot performing the greeting task by comprehensively considering the time, posture, and communication of customers entering the delivery environment; and the number of delivery tasks is predicted based on the customer flow data.

[0106] It should be noted that the robots performing the welcoming task can be specially designed welcoming robots, different from delivery robots; or they can be delivery robots that perform the welcoming task. Welcoming robots are generally located at the restaurant entrance, where they welcome, introduce, and guide guests entering the restaurant.

[0107] Here, the robot performing the welcoming task can identify the time, posture, and communication of customers entering the delivery environment, and thus determine the number of guests and tables. For example, it can identify guests who enter the delivery environment together as one table of guests; or identify guests who are facing each other while talking, or who are close to each other, or who are holding hands or engaging in other intimate actions as one table of guests.

[0108] Afterwards, each robot performing the greeting task sends its identified customer flow data to the cloud platform. The cloud platform aggregates the customer flow data from all robots and then predicts the number of delivery tasks based on a mapping relationship between customer flow data and the number of delivery tasks set according to historical experience. In this way, the cloud platform can link information from multiple robots, and through the integration and sharing of robot information, it can more timely control the switching of robot working modes.

[0109] In another example, the visual interaction component of the delivery robot includes a display screen; the display screen includes an information display screen and an operation interaction screen; when the operating parameters include the real-time position of the delivery robot, and the delivery task parameters include the execution status of the delivery task; the control method may further include:

[0110] For each delivery robot whose delivery task is in progress, the system determines whether there is a customer within the robot's predetermined range based on the robot's real-time location. If no customer is found, the system controls the information display screen of the delivery robot to turn off. When the system determines that the delivery robot is about to arrive at the delivery point based on its real-time location, the system controls the information display screen to turn on.

[0111] Here, for each delivery robot whose delivery task is in execution, the delivery robot is transporting the delivery items to the delivery point; by comparing the real-time location of the delivery robot with the location of the table where there are already customers, or by using the visual sensors on the delivery robot, it can be determined whether there are customers within the predetermined range of the delivery robot (such as on both sides of the road or within a certain range in front).

[0112] If a customer is present, the information display screen of the delivery robot remains on and displays information; if no customer is present, the information display screen can be turned off to reduce unnecessary power consumption; when the delivery robot's real-time location determines that it is about to arrive at the delivery point, the information display screen is turned on and displays information to fully ensure that the delivery robot can fulfill its advertising and display functions. In this embodiment, turning off the display screen includes either completely turning it off or reducing the screen brightness, both of which can achieve the effect of saving power; correspondingly, turning on the display screen includes either turning it on from completely off or increasing the screen brightness.

[0113] In another example, the control method may further include:

[0114] For any delivery point in the delivery environment, when it is detected that the delivery item has been at that delivery point for a preset time, the robot is controlled to switch from the current working mode to the full working mode to perform the retrieval task.

[0115] Similarly, the robots that perform recycling tasks can be specially designed recycling robots, which are a different type from delivery robots; or they can be delivery robots that perform recycling tasks.

[0116] Here, when the preset time has elapsed since the delivery items arrived at any delivery point, it is predicted that the customer has finished eating. At this point, a robot can be selected from the delivery environment and controlled to switch from its current working mode to full working mode to proceed to the delivery point to perform the collection task. When performing the collection task at the delivery point, the robot can autonomously collect the plates, garbage, etc., or it can assist with collection through voice prompts to service personnel; this application does not impose any limitations on this.

[0117] This application provides a control method for a delivery robot, which transports items from a pickup point to a delivery point when performing a delivery task. The control method is applied to a cloud platform and includes: determining a target delivery robot and its desired working mode from among the delivery robots based on the operating parameters of each delivery robot in the delivery environment and the delivery task parameters; wherein the delivery task parameters include at least one of the following: the production progress of the items to be delivered, the execution status of the delivery task, and the number of delivery tasks; controlling the target delivery robot to switch from the current working mode to the desired working mode; and controlling the switching states of different components in the delivery robot to implement different power-saving strategies under different working modes.

[0118] This approach addresses the issues of limited daily task capacity, low efficiency, and inability to promptly meet user needs in existing technologies. It enables precise utilization of delivery robot battery power, extends robot runtime, and ultimately improves robot efficiency.

[0119] Based on the same inventive concept, this application also provides a control device for a delivery robot. The delivery robot, when performing a delivery task, is used to transport items from a pickup point to a delivery point; the control device is applied to a cloud platform.

[0120] Please see Figure 2 , Figure 3 , Figure 2 This is one of the structural schematic diagrams of a control device for a delivery robot provided in an embodiment of this application. Figure 3 This is a second schematic diagram of the structure of a control device for a delivery robot provided in an embodiment of this application. Figure 2 As shown, the control device 200 includes:

[0121] The determining module 210 is used to determine the target delivery robot and the desired working mode of the target delivery robot from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment; wherein, the delivery task parameters include at least one of the following: the production progress of the delivery items, the execution status of the delivery task, and the number of delivery tasks.

[0122] The control module 220 is used to control the target delivery robot to switch from the current working mode to the desired working mode; in different working modes, by controlling the switching state of different components in the delivery robot, the delivery robot executes power-saving strategies with different levels of power saving.

[0123] Furthermore, when the operating parameters include the real-time location of the delivery robot and the placement signal of the delivery item, and the delivery task parameters include the production progress of the delivery item, the determining module 210 is specifically used for:

[0124] When the production progress indicator of the delivery item indicates the presence of a target delivery item, the first delivery robot in the waiting queue within the preset range of the pickup point is identified as the target delivery robot based on the real-time location of each delivery robot. The target delivery item is a delivery item whose estimated completion time is less than the current time, and the delivery robots in the waiting queue are in standby mode. In standby mode, the delivery item detection sensor, obstacle detection sensor, visual interaction component, and motion component of the delivery robot are all turned off.

[0125] The desired operating mode of the target delivery robot is determined to be the wake-up mode; in the wake-up mode, the delivery item detection sensor, obstacle detection sensor and motion component of the delivery robot are turned on, and the visual interaction component is turned off;

[0126] When the real-time location of the target delivery robot is detected to have reached the pickup point, and the delivery item placement signal is received from the delivery item detection sensor of the target delivery robot, the desired working mode of the target delivery robot is determined to be the full working mode; in the full working mode, the delivery item detection sensor, obstacle detection sensor, visual interaction component and motion component of the delivery robot are all turned on.

[0127] Furthermore, after identifying the first delivery robot in the waiting queue within the preset range of the pickup point as the target delivery robot, the determining module 210 is further configured to:

[0128] When it is determined that the quantity of the target delivery items is greater than the quantity of delivery items that the current target delivery robot can carry, the number of additional delivery robots needed is predicted based on the quantity of the target delivery items.

[0129] Based on the number of delivery robots still needed, the remaining number of other delivery robots in the waiting queue are sequentially determined as the target delivery robots, and the expected working mode of the other delivery robots is sequentially determined as the wake-up mode.

[0130] Furthermore, when the delivery task parameters also include the execution status of the delivery task, the determining module 210 is specifically used for:

[0131] When it is detected that the real-time location of the current target delivery robot has left the pickup point and the delivery task is in execution status, the other delivery robots in the waiting queue are sequentially identified as the target delivery robot, and the expected working mode of the other delivery robots is sequentially identified as the wake-up mode.

[0132] When it is detected that other delivery robots in the wake-up mode have moved sequentially to the original position of the previous delivery robot in the waiting queue, if the production progress indicator of the delivery item does not contain the target delivery item, the expected working mode of the other delivery robots is redefined as the standby mode.

[0133] Furthermore, when the operating parameters include the real-time battery level and real-time location of the delivery robot, and the delivery task parameters include the execution status of the delivery task, the determining module 210 is specifically used for:

[0134] When the execution status of any delivery robot's delivery task changes from "in execution" to "completed", that delivery robot is identified as the target delivery robot, and the desired working mode is set to "return mode". In the return mode, the obstacle detection sensor, visual interaction component, and motion component of the delivery robot are turned on, while the delivery item detection sensor is turned off.

[0135] Determine whether the real-time battery level of the target delivery robot is lower than a first preset battery threshold.

[0136] If the battery level is below the first preset threshold, the target delivery robot is controlled to move to the charging point based on its real-time location.

[0137] Once the real-time location of the target delivery robot is determined to have reached the charging point, the desired operating mode is set to charging mode. In the charging mode, the charging indicator light in the visual interaction component of the delivery robot is turned on, while the delivery item detection sensor, obstacle detection sensor, motion component, and other visual interaction components are all turned off.

[0138] Furthermore, the determining module 210 is also used for:

[0139] If the power level is not lower than the first preset power threshold, then the target delivery robot is controlled to move to the end of the waiting queue based on its real-time position.

[0140] Once the real-time location of the target delivery robot is determined to have reached the end of the waiting queue, the desired working mode is set to standby mode.

[0141] Furthermore, when the operating parameters include the real-time battery level of the delivery robot, and the delivery task parameters include the number of delivery tasks, the determining module 210 is specifically used for:

[0142] When the number of delivery tasks is predicted to increase, the delivery robot that is in the charging mode and has a real-time battery level higher than the second preset battery level threshold will be identified as the target delivery robot.

[0143] The desired operating mode of the target delivery robot is set to wake-up mode to control the target delivery robot to move towards the pickup point.

[0144] Furthermore, the determining module 210 is also used for:

[0145] When it is determined that the number of delivery tasks is less than a preset quantity threshold or the number of delivery tasks is predicted to decrease, other delivery robots other than the first robot in the waiting queue within the preset range of the pickup point are identified as the target delivery robots.

[0146] The desired operating mode of the target delivery robot is determined to be standby mode.

[0147] Furthermore, such as Figure 3 As shown, the control device 200 further includes a prediction module 230; the prediction module 230 is used to predict the quantity of the delivery tasks in the following manner:

[0148] Receive customer flow data sent by the robot performing the greeting task; wherein, the customer flow data is determined by the robot performing the greeting task by taking into account the time when the customer enters the delivery environment, their posture and interaction.

[0149] The number of delivery tasks is predicted based on the passenger flow data.

[0150] Furthermore, the visual interaction component of the delivery robot includes a display screen; the display screen includes an information display screen and an operation interaction screen; the control module 220 is also used for:

[0151] For each delivery robot whose delivery task is in progress, determine whether there are customers within the robot's designated area.

[0152] If it does not exist, then the information display screen of the delivery robot will be turned off;

[0153] When it is determined that the delivery robot is about to arrive at the delivery point based on its real-time location, the information display screen is turned on.

[0154] Furthermore, such as Figure 3 As shown, the control device 200 further includes a recycling module 240; the recycling module 240 is used for:

[0155] For any delivery point in the delivery environment, when it is detected that the delivery item has been at that delivery point for a preset time, the robot is controlled to switch from the current working mode to the full working mode to perform the retrieval task.

[0156] It should be noted that the specific implementation of the device can be found in the method embodiment. Since the principle of the control device in this application embodiment is similar to the control method described above in this application embodiment, the implementation of the device can be found in the implementation of the method, and repeated details will not be repeated.

[0157] Based on the same inventive concept, this application also provides a delivery system in its embodiments. Please refer to... Figure 4 , Figure 2 This is a schematic diagram of a delivery system provided in an embodiment of this application. Figure 4As shown, the delivery system 400 includes delivery robots A1, Ai, ..., An (i and n are positive integers) and a cloud platform 410; the delivery robots A1, ..., Ai, ..., An are communicatively connected to the cloud platform 410.

[0158] The cloud platform 410 is used to determine a target delivery robot and its desired working mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment; and to control the target delivery robot to switch from its current working mode to the desired working mode; wherein, the delivery task parameters include at least one of the following: the production progress of the delivered items, the execution status of the delivery task, and the number of delivery tasks; and in different working modes, the delivery robot executes power-saving strategies of different power-saving levels by controlling the switching states of different components in the delivery robot;

[0159] The delivery robots A1, Ai, ... An are used to switch from the current working mode to the desired working mode under the control of the cloud platform.

[0160] This application also provides an electronic device, including a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they can perform the operations described above. Figure 1 The steps of a control method for a delivery robot shown in the method embodiment are described in detail in the method embodiment, and will not be repeated here.

[0161] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described actions. Figure 1 The steps of a control method for a delivery robot shown in the method embodiment are described in detail in the method embodiment, and will not be repeated here.

[0162] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0163] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0164] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0165] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0166] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0167] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The scope of protection of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A control method for a delivery robot, characterized in that, The delivery robot is used to transport items from the pickup point to the delivery point when performing delivery tasks. The control method is applied to a cloud platform, and the control method includes: Based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment, a target delivery robot and its expected working mode are determined from among the delivery robots; wherein, the delivery task parameters include at least one of the following: the production progress of the delivery items, the execution status of the delivery task, and the number of delivery tasks; The target delivery robot is controlled to switch from the current working mode to the desired working mode; in different working modes, the delivery robot executes power-saving strategies of different power-saving levels by controlling the switching states of different components in the delivery robot; When the operating parameters include the real-time location of the delivery robot and the delivery item placement signal, and the delivery task parameters include the production progress of the delivery item, the step of determining the target delivery robot and its desired operating mode from among the delivery robots based on the operating parameters of each delivery robot in the delivery environment and the delivery task parameters includes: When the production progress indicator of the delivery item indicates the presence of a target delivery item, the first delivery robot in the waiting queue within the preset range of the pickup point is identified as the target delivery robot based on the real-time location of each delivery robot. The target delivery item is a delivery item whose estimated completion time is less than the current time, and the delivery robots in the waiting queue are in standby mode. In standby mode, the delivery item detection sensor, obstacle detection sensor, visual interaction component, and motion component of the delivery robot are all turned off. The desired operating mode of the target delivery robot is determined to be the wake-up mode; in the wake-up mode, the delivery item detection sensor, obstacle detection sensor and motion component of the delivery robot are turned on, and the visual interaction component is turned off; When the real-time location of the target delivery robot is detected to have reached the pickup point, and the delivery item placement signal is received from the delivery item detection sensor of the target delivery robot, the desired working mode of the target delivery robot is determined to be the full working mode; in the full working mode, the delivery item detection sensor, obstacle detection sensor, visual interaction component and motion component of the delivery robot are all turned on.

2. The control method according to claim 1, characterized in that, After identifying the first delivery robot in the waiting queue within the preset range of the pickup point as the target delivery robot, the step of determining the target delivery robot and its desired operating mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment further includes: When it is determined that the quantity of the target delivery items is greater than the quantity of delivery items that the current target delivery robot can carry, the number of additional delivery robots needed is predicted based on the quantity of the target delivery items. Based on the number of delivery robots still needed, the remaining number of other delivery robots in the waiting queue are sequentially determined as the target delivery robots, and the expected working mode of the other delivery robots is sequentially determined as the wake-up mode.

3. The control method according to claim 1 or 2, characterized in that, When the delivery task parameters also include the execution status of the delivery task, the step of determining the target delivery robot and its desired operating mode from among the delivery robots based on the operating parameters of each delivery robot in the delivery environment and the delivery task parameters further includes: When it is detected that the real-time location of the current target delivery robot has left the pickup point and the delivery task is in execution status, the other delivery robots in the waiting queue are sequentially identified as the target delivery robot, and the expected working mode of the other delivery robots is sequentially identified as the wake-up mode. When it is detected that other delivery robots in the wake-up mode have moved sequentially to the original position of the previous delivery robot in the waiting queue, if the production progress indicator of the delivery item does not contain the target delivery item, the expected working mode of the other delivery robots is redefined as the standby mode.

4. The control method according to claim 1, characterized in that, When the operating parameters include the real-time battery level and real-time location of the delivery robot, and the delivery task parameters include the execution status of the delivery task, the step of determining the target delivery robot and its desired operating mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment includes: When the execution status of any delivery robot's delivery task changes from "in execution" to "completed", that delivery robot is identified as the target delivery robot, and the desired working mode is set to "return mode". In the return mode, the obstacle detection sensor, visual interaction component, and motion component of the delivery robot are turned on, while the delivery item detection sensor is turned off. Determine whether the real-time battery level of the target delivery robot is lower than a first preset battery threshold. If the battery level is below the first preset threshold, the target delivery robot is controlled to move to the charging point based on its real-time location. Once the real-time location of the target delivery robot is determined to have reached the charging point, the desired operating mode is set to charging mode. In the charging mode, the charging indicator light in the visual interaction component of the delivery robot is turned on, while the delivery item detection sensor, obstacle detection sensor, motion component, and other visual interaction components are all turned off.

5. The control method according to claim 4, characterized in that, The step of determining the target delivery robot and its desired operating mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment also includes: If the power level is not lower than the first preset power threshold, then the target delivery robot is controlled to move to the end of the waiting queue based on its real-time position. Once the real-time location of the target delivery robot is determined to have reached the end of the waiting queue, the desired working mode is set to standby mode.

6. The control method according to claim 4, characterized in that, When the operating parameters include the real-time battery level of the delivery robot, and the delivery task parameters include the number of delivery tasks, determining the target delivery robot and its desired operating mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment includes: When the number of delivery tasks is predicted to increase, the delivery robot that is in the charging mode and has a real-time battery level higher than the second preset battery level threshold will be identified as the target delivery robot. The desired operating mode of the target delivery robot is set to wake-up mode to control the target delivery robot to move towards the pickup point.

7. The control method according to claim 6, characterized in that, The step of determining the target delivery robot and its desired operating mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment also includes: When it is determined that the number of delivery tasks is less than a preset quantity threshold or the number of delivery tasks is predicted to decrease, other delivery robots other than the first robot in the waiting queue within the preset range of the pickup point are identified as the target delivery robots. The desired operating mode of the target delivery robot is determined to be standby mode.

8. The control method according to any one of claims 6 or 7, characterized in that, The quantity of the delivery tasks is predicted using the following method: Receive customer flow data sent by the robot performing the greeting task; wherein, the customer flow data is determined by the robot performing the greeting task by taking into account the time when the customer enters the delivery environment, their posture and interaction. The number of delivery tasks is predicted based on the passenger flow data.

9. The control method according to claim 1, characterized in that, The visual interaction component of the delivery robot includes a display screen; the display screen includes an information display screen and an operation interaction screen; The control method further includes: For each delivery robot whose delivery task is in progress, determine whether there are customers within the robot's designated area. If it does not exist, then the information display screen of the delivery robot will be turned off; When it is determined that the delivery robot is about to arrive at the delivery point based on its real-time location, the information display screen is turned on.

10. The control method according to claim 1, characterized in that, The control method further includes: For any delivery point in the delivery environment, when it is detected that the delivery item has been at that delivery point for a preset time, the robot is controlled to switch from the current working mode to the full working mode to perform the retrieval task.

11. A control device for a delivery robot, characterized in that, The delivery robot is used to transport items from the pickup point to the delivery point when performing delivery tasks. The control device is applied to a cloud platform, and the control device includes: The determination module is used to determine the target delivery robot and its expected working mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment; wherein, the delivery task parameters include at least one of the following: the production progress of the delivery items, the execution status of the delivery task, and the number of delivery tasks. The control module is used to control the target delivery robot to switch from the current working mode to the desired working mode; in different working modes, the delivery robot executes power-saving strategies of different power-saving levels by controlling the switching states of different components in the delivery robot; When the operating parameters include the real-time location of the delivery robot and the placement signal of the delivered items, and the delivery task parameters include the production progress of the delivered items, the determining module is specifically used for: When the production progress indicator of the delivery item indicates the presence of a target delivery item, the first delivery robot in the waiting queue within the preset range of the pickup point is identified as the target delivery robot based on the real-time location of each delivery robot. The target delivery item is a delivery item whose estimated completion time is less than the current time, and the delivery robots in the waiting queue are in standby mode. In standby mode, the delivery item detection sensor, obstacle detection sensor, visual interaction component, and motion component of the delivery robot are all turned off. The desired operating mode of the target delivery robot is determined to be the wake-up mode; in the wake-up mode, the delivery item detection sensor, obstacle detection sensor and motion component of the delivery robot are turned on, and the visual interaction component is turned off; When the real-time location of the target delivery robot is detected to have reached the pickup point, and the delivery item placement signal is received from the delivery item detection sensor of the target delivery robot, the desired working mode of the target delivery robot is determined to be the full working mode; in the full working mode, the delivery item detection sensor, obstacle detection sensor, visual interaction component and motion component of the delivery robot are all turned on.

12. A delivery system, characterized in that, The delivery system includes a delivery robot and a cloud platform; the delivery robot is communicatively connected to the cloud platform; the cloud platform is used to execute the steps of the control method as described in any one of claims 1 to 10; The cloud platform is used to determine the target delivery robot and its desired working mode from among the delivery robots based on the operating parameters and delivery task parameters of each delivery robot in the delivery environment; and to control the target delivery robot to switch from the current working mode to the desired working mode; wherein, the delivery task parameters include at least one of the following: the production progress of the delivered items, the execution status of the delivery task, and the number of delivery tasks; and in different working modes, the delivery robot executes power-saving strategies with different levels of power saving by controlling the on / off states of different components in the delivery robot; The delivery robot is used to switch from the current working mode to the desired working mode under the control of the cloud platform.

Images