Charging method and device for transfer robot

Abstract

The invention discloses a charging method and device for a transfer robot, and relates to the technical field of automatic control. The method can comprise the following steps: acquiring the moving distance information of a to-be-executed carrying task of the carrying robot; based on the distance information, power consumption information of the transfer robot is determined, and the power consumption information is used for representing power consumed by the transfer robot for executing the transfer task; in response to the fact that the electric quantity information of the transfer robot is smaller than or equal to the electric quantity consumption information, the charging path of the transfer robot is determined based on the position information of the transfer robot, the electric quantity information is used for representing the electric quantity allowed to be consumed by the transfer robot, and charging equipment is deployed at the end point of the charging path; and according to the charging path, the transfer robot is controlled to move to the charging equipment to be charged, and in the process that the transfer robot is charged by the charging equipment, the transfer robot is in a no-load state. The technical problem that the charging safety of the transfer robot is low is solved.

Description

Technical Field

[0001] The present application relates to the field of automation control technology, and in particular to a charging method and device for a handling robot. Background Art

[0002] At present, the charging method of existing handling robots is usually that when the power of the handling robot is lower than the power threshold, the handling robot goes to the charging pile or charging station to charge by itself. This requires the handling robot to be equipped with a positioning system and a navigation system so that the handling robot can automatically move to the charging position.

[0003] However, this method poses a great safety hazard to handling robots that carry flammable and explosive goods. If the handling robot is charged only by setting the power level of the handling robot to be lower than the power threshold, some handling robots may carry explosives to the charging pile while in the handling state. Due to static electricity or contact discharge of the interface, abnormal discharge sparks may occur during charging, resulting in a technical problem of low safety in charging the handling robot.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a charging method and device for a transport robot, so as to at least solve the technical problem of low safety in charging the transport robot.

[0006] According to one aspect of an embodiment of the present application, a charging method for a transport robot is provided. The method may include: obtaining information about the distance that the transport robot moves to perform a transport task; based on the distance information, determining the power consumption information of the transport robot, wherein the power consumption information is used to indicate the amount of power required to be consumed by the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, determining the charging path of the transport robot based on the position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; controlling the transport robot to move to the charging device for charging according to the charging path, wherein the transport robot is in an unloaded state during the process of the charging device charging the transport robot.

[0007] Optionally, based on the position information of the transport robot, the charging path of the transport robot is determined, including: determining the passage area of ​​the transport robot based on the size information of the transport robot and the environmental information of the transport robot; based on the passage area, determining multiple passage positions through which the transport robot will perform the transport task; based on the position information and the multiple passage positions, determining the charging path.

[0008] Optionally, determining a charging path based on location information and multiple pass locations includes: determining a target pass location from multiple pass locations based on the location information; determining a charging position of a charging device based on the target pass location; and generating a charging path based on the target pass location and the charging position of the charging device.

[0009] Optionally, the method includes: obtaining a rolling resistance and an acceleration force of a transporting task to be performed by the transporting robot; and determining an energy consumption rate of the transporting robot based on the rolling resistance and the acceleration force.

[0010] Optionally, determining the power consumption information of the transport robot based on the distance information includes: determining the power consumption information of the transport robot based on the distance information and the energy consumption rate.

[0011] Optionally, based on the distance information and the energy consumption rate, the power consumption information of the transport robot is determined, including: calling a neural network model, calibrating the energy consumption rate, and obtaining a target energy consumption rate, wherein the neural network model is trained based on energy consumption rate samples; based on the distance information and the target energy consumption rate, the power consumption information of the transport robot is determined.

[0012] Optionally, after controlling the transport robot to move to the charging device for charging according to the charging path, the method also includes: monitoring the charging status of the transport robot; in response to the charging status being a charging completion state, controlling the transport robot to move to a target area according to a return path corresponding to the charging path, wherein the target area is located at the starting point of the charging path, and the target area is located at the end point of the return path.

[0013] Optionally, the method further includes: in response to the power information of the transport robot being greater than the power consumption information, controlling the transport robot to perform the transport task.

[0014] Optionally, the method further includes: in the process of controlling the transport robot to perform the transport task, in response to the power information being less than or equal to the power consumption information and the transport robot being in a no-load state, charging the transport robot with a backup battery.

[0015] According to another aspect of the embodiment of the present application, a charging device for a handling robot is also provided. The device may include: an acquisition unit, used to acquire the distance information of the handling robot to perform the handling task; a first determination unit, used to determine the power consumption information of the handling robot based on the distance information, wherein the power consumption information is used to indicate the power required to be consumed by the handling robot to perform the handling task; a second determination unit, used to determine the charging path of the handling robot based on the position information of the handling robot in response to the power information of the handling robot being less than or equal to the power consumption information, wherein the power information is used to indicate the power allowed to be consumed by the handling robot, and a charging device is deployed at the end of the charging path; a charging unit, used to control the handling robot to move to the charging device for charging according to the charging path, wherein the handling robot is in an unloaded state during the process of the charging device charging the handling robot.

[0016] According to another aspect of an embodiment of the present application, a non-volatile storage medium is also provided, including: the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute any one of the charging methods for the transport robot.

[0017] According to another aspect of an embodiment of the present invention, a processor is further provided, and the processor is used to run a program, wherein the charging method for the transport robot in the embodiment of the present invention is executed when the program is run.

[0018] According to another aspect of an embodiment of the present application, there is also provided an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute instructions to implement any one of the charging methods for a transport robot.

[0019] According to another aspect of the embodiment of the present application, a computer program product is further provided. The computer program product may include a computer program, wherein the computer program is configured to execute any of the above-mentioned charging methods for a transport robot when running.

[0020] According to another aspect of the embodiment of the present application, a computer program product is also provided. The computer program product may include a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and the computer program is configured to execute any of the above-mentioned charging methods for a handling robot when running.

[0021] According to another aspect of the embodiment of the present application, a computer program is further provided, wherein the computer program is configured to execute any one of the above-mentioned charging methods for the transport robot when running.

[0022] In an embodiment of the present application, information on the distance moved by a transport robot to perform a transport task is obtained; based on the distance information, power consumption information of the transport robot is determined, wherein the power consumption information is used to indicate the amount of power required for the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, a charging path of the transport robot is determined based on position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; the transport robot is controlled to move to the charging device for charging according to the charging path, wherein, during the process of the charging device charging the transport robot, the transport robot is in an unloaded state, thereby achieving the technical effect of improving the safety of charging the transport robot, thereby solving the technical problem of low safety in charging the transport robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0024] Figure 1 is a flow chart of a charging method for a transport robot according to an embodiment of the present application;

[0025] Figure 2 It is a flow chart of a charging management method of an intelligent transport robot according to an embodiment of the present application;

[0026] Figure 3 is a structural schematic diagram of a charging device for a transport robot according to an embodiment of the present application;

[0027] Figure 4 is a schematic block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the present application, the technical solutions 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 should fall within the scope of protection of this application.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] According to an embodiment of the present application, a method embodiment of a charging method for a transport robot is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] Figure 1 is a flow chart of a charging method for a transport robot according to an embodiment of the present application, such as Figure 1 As shown, the method may include the following steps:

[0032] Step S102, obtaining information on the distance moved by the transport robot to perform the transport task.

[0033] In the technical solution provided in the above step S102, the distance information of the transport robot to be moved to perform the transport task can be obtained. The transport robot can be an intelligent transport robot. The distance information can be used to indicate the distance that the transport robot needs to move to perform the transport task, and can also be called transport distance information.

[0034] Optionally, the handling task information of the handling task to be performed by the handling robot is obtained, and the handling task information may at least include the handling distance information. The handling task information is generated or stored in the intelligent warehouse management platform, and each handling robot is communicatively connected to the intelligent warehouse management platform. The handling task information generated for each handling task may at least include: authorized operator information, handling starting point location information, warehouse number information, explosive item information, explosive package size information, explosive package weight information, etc. After the handling task information is determined, the handling robot may first obtain the handling task information, and further calculate the handling distance information based on the warehouse number information and handling starting point location information in the handling task information.

[0035] It should be noted that each handling task performed by the handling robot requires the participation of an operator, and the operator information may at least include the operator's identity information, authorized operation warehouse number, etc. The explosive size information refers to the length, width, height and volume of the explosive package.

[0036] Step S104: determining the power consumption information of the transport robot based on the distance information, wherein the power consumption information is used to indicate the power consumed by the transport robot to perform the transport task.

[0037] In the technical solution provided in the above step S104, after obtaining the distance information of the transport robot to be moved to perform the transport task, the power consumption information of the transport robot can be determined based on the obtained distance information. The power consumption information can be used to indicate the power consumed by the transport robot to perform the transport task, and can also be called single power consumption information.

[0038] Optionally, after obtaining the transport distance information of the transport robot to perform the transport task, the single power consumption information of the transport robot performing the transport task can be determined based on the transport distance information and the energy consumption rate of the transport robot.

[0039] It should be noted that the power consumption of the handling robot is directly related to the handling distance. In order to avoid potential safety hazards caused by charging, the charging equipment (i.e., charging piles) in this embodiment are all set at a place outside the minimum safe distance from the explosive warehouse. At the same time, in order to avoid triggering the charging strategy during transportation, this embodiment first evaluates the single power consumption, and then compares the single power consumption with the remaining power to estimate whether the remaining power is sufficient to complete the next transportation. If the remaining power cannot complete the next transportation, go directly to the charging pile for charging. Among them, when evaluating the single power consumption, the preset energy consumption rate calibrated by the handling robot when it leaves the factory can be relied on for calculation. At this time, the single power consumption can be obtained directly by multiplying the energy consumption rate by the handling distance.

[0040] Step S106, in response to the power information of the transport robot being less than or equal to the power consumption information, determining the charging path of the transport robot based on the position information of the transport robot, wherein the power information is used to indicate the power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path.

[0041] In the technical solution provided in the above step S106, after determining the power consumption information of the transport robot, the power consumption information of the transport robot can be compared with the power information of the transport robot. When the power information of the transport robot is less than or equal to the power consumption information, the charging path of the transport robot is determined based on the position information of the transport robot. Among them, the power information can be used to indicate the amount of power allowed to be consumed by the transport robot, which can be referred to as remaining power information. The position information can be used to indicate the current position of the transport robot, which can be referred to as current position information. A charging device is deployed at the end of the charging path, and the charging device can be a charging pile.

[0042] Optionally, after determining the power consumption information of the transport robot, the remaining power information of the transport robot can be obtained in real time. When the remaining power information is greater than the single power consumption information, the transport task is performed. When the remaining power information is less than or equal to the single power consumption information, the current position information of the transport robot is obtained, and the charging path and the return path are generated according to the current position information and the preset charging pile position.

[0043] Step S108, controlling the transport robot to move to the charging device for charging according to the charging path, wherein the transport robot is in an unloaded state during the process of the charging device charging the transport robot.

[0044] In the technical solution provided in the above step S108, after determining the charging path of the transport robot, the transport robot can be controlled to move to the charging device for charging according to the charging path. In the process of the charging device charging the transport robot, the transport robot is in an unloaded state, and the unloaded state can be used to indicate that no explosives or other items are placed in the transport robot during the charging process, thereby preventing abnormal discharge sparks from occurring when the transport robot is charging.

[0045] Optionally, after determining the charging path of the transport robot, the transport robot can be controlled to go to the charging pile for charging according to the charging path, and the charging status of the transport robot can be monitored in real time. After the charging of the transport robot is completed, the transport robot can be controlled to return to the transport point according to the return path. The return path can be a path opposite to the starting point and the end point of the charging path.

[0046] In an embodiment of the present application, information on the distance moved by a transport robot to perform a transport task is obtained; based on the distance information, power consumption information of the transport robot is determined, wherein the power consumption information is used to indicate the amount of power required for the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, a charging path of the transport robot is determined based on position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; the transport robot is controlled to move to the charging device for charging according to the charging path, wherein, during the process of the charging device charging the transport robot, the transport robot is in an unloaded state, thereby achieving the technical effect of improving the safety of charging the transport robot, thereby solving the technical problem of low safety in charging the transport robot.

[0047] The above embodiments of the present application are further described below.

[0048] In some embodiments of the present application, step S106, based on the position information of the transport robot, determines the charging path of the transport robot, including: determining the passage area of ​​the transport robot based on the size information of the transport robot and the environmental information of the transport robot; based on the passage area, determining multiple passage positions through which the transport robot will perform the transport task; based on the position information and the multiple passage positions, determining the charging path.

[0049] In this embodiment, the passage area of ​​the transport robot can be determined based on the size information of the transport robot and the environmental information of the transport robot. After determining the passage area of ​​the transport robot, multiple passage positions through which the transport robot is to perform the transport task can be determined. Further based on the position information of the transport robot and the multiple passage positions, the charging path can be determined. Among them, the size information can be used to represent information such as the length and width of the working area of ​​the transport cart on the transport robot. The environmental information of the transport robot can be used to represent information such as the coordinate position and area of ​​static obstacles (stacking area) in the environment. The passage position can be used to represent the intermediate nodes passed by the transport robot.

[0050] Optionally, determine the length and width and other dimensional information of the working area of ​​the transport cart on the transport robot, and determine the coordinate position and area and other environmental information of the static obstacle (stacking area) in the environment. Create a grid map, divide the working area of ​​the transport cart into grids, each grid is defined as a grid, and each grid identifies a position and a state. Among them, the state refers to occupied or passable. For example, if the grid coincides with a static obstacle, the state is set to occupied or impassable, that is, based on the above-mentioned dimensional information and environmental information, the pass area of ​​the transport robot can be determined.

[0051] Furthermore, a graph model of nodes and edges is established, the above grid map is converted into an image, and the nodes and edges are marked in the image. Among them, the nodes include target nodes and intermediate nodes. The target node refers to the fixed charging pile position, the intermediate node refers to the location point where the route needs to turn at the static obstacle, that is, the pass position, and the edge refers to the straight line connecting the adjacent nodes without crossing the obstacle grid. In the pass area, after determining the multiple pass positions that the handling robot passes through to perform the handling task, the charging path can be determined based on the position information and the multiple pass positions.

[0052] It should be noted that when the transport robot is carrying, it follows a preset fixed path, and when charging is needed, it goes from a non-fixed position to a fixed charging pile, and the path needs to be dynamically generated. The warehouse in this embodiment is a fixed scene, and generally charging piles are deployed at the four corners of the warehouse, and the positions of the charging piles are also fixed. When generating the charging path and the return path, in fact, only the charging path is generated. The return path is the same as the charging path, but the direction of travel changes.

[0053] In some embodiments of the present application, a charging path is determined based on location information and multiple pass locations, including: determining a target pass location from multiple pass locations based on the location information; determining a charging position of a charging device based on the target pass location; and generating a charging path based on the target pass location and the charging position of the charging device.

[0054] In this embodiment, after determining multiple pass positions, based on the position information of the transport robot, a target pass position can be determined from the multiple pass positions. After determining the target pass position, based on the determined target pass position, a charging position of the charging device can be determined. Further based on the target pass position and the charging position of the charging device, a charging path can be generated. The target pass position can be an intermediate node closest to the position information.

[0055] Optionally, the distance between each intermediate node and the target node (i.e., the charging position) is calculated to determine the nearest target node and edge to each intermediate node. The position information of the transport vehicle is determined based on the positioning, and the nearest intermediate node is determined based on the position information. The nearest target node is determined based on the nearest intermediate node, that is, the nearest charging pile is determined. A charging path is generated according to the edge between the nearest intermediate node and the target node. The specific algorithm is a heuristic search algorithm (e.g., A* algorithm). Among them, the A* algorithm is suitable for path planning problems, combining the advantages of finding the shortest path algorithm (Dijkstra algorithm) and the advantages of heuristic search (i.e., reducing the search space and improving efficiency).

[0056] In some embodiments of the present application, the method includes: obtaining the rolling resistance and acceleration force of the transport robot to perform a transport task; and determining the energy consumption rate of the transport robot based on the rolling resistance and the acceleration force.

[0057] In this embodiment, the rolling resistance and acceleration force of the handling task to be performed by the handling robot can be obtained, and the energy consumption rate of the handling robot can be determined based on the obtained rolling resistance and acceleration force. There is a correlation between the weight and energy consumption of the handling trolley of the handling robot, and the correlation is the process of calibrating the energy consumption rate, that is, under a fixed warehouse floor environment, a fixed rolling resistance coefficient, the total mass of the handling trolley and the unit load, and a fixed transfer station position to the target position, the energy consumption rate of a single handling is determined.

[0058] Optionally, the rolling resistance of the handling robot to perform the handling task can be expressed by the following formula: rolling resistance = rolling resistance coefficient × total mass of the load × acceleration of gravity. The acceleration force of the handling robot to perform the handling task can be expressed by the following formula: acceleration force = total mass of the load × acceleration of gravity. The energy consumption rate of the handling robot can be expressed by the following formula: energy consumption aluminum = (rolling resistance + acceleration force) × travel speed / operation time.

[0059] In some embodiments of the present application, step S104, determining the power consumption information of the transport robot based on the distance information, includes: determining the power consumption information of the transport robot based on the distance information and the energy consumption rate.

[0060] In this embodiment, after obtaining the transport distance information of the transport robot to perform the transport task, the single power consumption information of the transport robot performing the transport task can be determined based on the transport distance information and the energy consumption rate of the transport robot.

[0061] In some embodiments of the present application, the power consumption information of the transport robot is determined based on the distance information and the energy consumption rate, including: calling a neural network model, calibrating the energy consumption rate, and obtaining a target energy consumption rate, wherein the neural network model is trained based on energy consumption rate samples; based on the distance information and the target energy consumption rate, the power consumption information of the transport robot is determined.

[0062] In this embodiment, the neural network model can be called to calibrate the energy consumption rate to obtain the target energy consumption rate. Further based on the distance information and the target energy consumption rate, the power consumption information of the transport robot can be determined. The neural network model can be obtained by training based on the energy consumption rate sample.

[0063] Optionally, the preset energy consumption rate calibrated by the handling robot when it leaves the factory is usually a calibration value under specific conditions and cannot fully represent the working environment. Therefore, this embodiment also recalibrates the energy consumption rate. After obtaining the remaining power information of the handling robot, when the remaining power information is greater than the first preset value (for example, 80%), the power consumption of the handling robot when performing a single handling task is monitored in real time through an electric energy meter or a current sensor, and the corresponding power consumption data is recorded, that is, the electric energy consumed by the handling robot at one time when carrying specific goods. The collected power consumption data is analyzed, the actual power consumption of the handling robot during the handling and returning journeys is calculated, and a calibration data set is generated based on the actual power consumption of multiple handling robots.

[0064] Furthermore, based on the calibration data set, a mathematical model of power consumption is established, and the energy consumption rate is recalibrated based on the mathematical model to obtain the actual energy consumption rate. The mathematical model can be a linear model or a nonlinear model. Since the linear model is generally not accurate, for the nonlinear model, this embodiment specifically adopts a polynomial model, an exponential model, a logarithmic model or a neural network model. Preferably, this embodiment adopts a neural network model, which can fit the relationship between the robot's energy consumption and the working state through a neural network structure. The construction of the model itself is similar to the existing model structure, including an input layer, a hidden layer, an output layer, connection weights, an activation function and a loss function.

[0065] The input layer receives external input data and passes it to the neural network. Each input node corresponds to a feature or attribute of the input data, and the number of nodes in the input layer depends on the dimension of the input data. The hidden layer is located between the input layer and the output layer, and is the part of the neural network that performs nonlinear transformation and feature extraction. A neural network can contain one or more hidden layers, each of which contains multiple neurons (nodes). The output layer receives the output of the hidden layer and produces the final prediction result or classification result. The number of nodes in the output layer depends on the output type of the model. For example, if it is a regression problem, there is usually only one output node; if it is a classification problem, the number of output nodes is usually equal to the number of categories. Connection weights are parameters in the neural network that are used to adjust the connection strength between neurons. Each connection has a weight value that represents the connection strength between the input node and the output node. These weight values ​​need to be learned and adjusted during the training process. The activation function (for example, Sigmoid, ReLU, Tanh) is a nonlinear transformation function used by each neuron in the hidden layer and the output layer to convert the weighted sum of the input to the output of the neuron. The loss function is used to measure the difference between the model's prediction result and the true label. During the training process, the neural network adjusts the connection weights by minimizing the loss function to improve the model's prediction accuracy.

[0066] After the neural network model is constructed, the model can be trained using the calibration data set as the training set: the neural network model is initialized using the pre-trained initial connection weights; the calibration data set is used as input data for forward propagation through the neural network, and the output value of each neuron is calculated layer by layer. During the forward propagation process, each neuron calculates the output value through the activation function based on the input data and the connection weight; the output result of the neural network is compared with the true label to calculate the value of the loss function; the connection weights in the neural network are adjusted through the loss function to minimize the loss function value; the connection weights in the neural network are updated using an optimization algorithm (for example, SGD, Adam, Adagrad, etc.), where SGD is used to represent stochastic gradient descent; the process of forward propagation, loss function calculation, back propagation, and parameter update is repeated until the stopping condition is reached. The stopping condition can be that the maximum number of iterations is reached and the loss function value converges to a smaller value.

[0067] In some embodiments of the present application, after controlling the transport robot to move to the charging device for charging according to the charging path, the method further includes: monitoring the charging status of the transport robot; in response to the charging status being a charging completion state, controlling the transport robot to move to a target area according to a return path corresponding to the charging path, wherein the target area is located at the starting point of the charging path, and the target area is located at the end point of the return path.

[0068] In this embodiment, after the handling robot is controlled to move to the charging device for charging according to the charging path, the charging state of the handling robot can be monitored. When the charging state is the charging completion state, the handling robot is controlled to move to the target area according to the return path corresponding to the charging path. The target area can be located at the starting point of the charging path, and the target area is located at the end point of the return path. The target area can be a handling area or a handling point.

[0069] Optionally, after determining the charging path of the transport robot, the transport robot can be controlled to go to the charging pile for charging according to the charging path, and the charging status of the transport robot can be monitored in real time. After the charging of the transport robot is completed, the transport robot can be controlled to return to the transport point according to the return path. The return path can be a path opposite to the starting point and the end point of the charging path.

[0070] In some embodiments of the present application, the method further includes: in response to the power information of the transport robot being greater than the power consumption information, controlling the transport robot to perform the transport task.

[0071] In this embodiment, after the power consumption information of the transport robot is determined, the remaining power information of the transport robot can be obtained in real time. When the remaining power information is greater than the single power consumption information, the transport task is executed.

[0072] In some embodiments of the present application, the method further includes: in the process of controlling the transport robot to perform a transport task, in response to the power information being less than or equal to the power consumption information and the transport robot being in an unloaded state, charging the transport robot with a backup battery.

[0073] In this embodiment, during the process of controlling the transport robot to perform a transport task, when the power information of the transport robot is less than or equal to the power consumption information and the transport robot is in an unloaded state, the backup battery can be used to charge the transport robot.

[0074] Optionally, due to battery aging factors, the remaining power information of some transport robots may not be accurate, that is, at the beginning of a single transport, the initial assessment can complete a single transport, but the battery decays rapidly during the transport, so that before reaching the end of the transport, the battery power reaches the minimum preset value, and the minimum preset value can only support the empty return trip and system control operation of the transport robot. Therefore, this embodiment considers adding a backup battery to the transport robot to solve the problem, or also considers switching the transport robot to a rescue mode and sending a low-power distress signal and current location information at the same time. The intelligent warehouse management platform dispatches the nearest transport robot to the rescue according to the current location information of the low-power transport robot, and relays the transportation of explosives.

[0075] It should be noted that when dispatching the nearest transport robot to go to the rescue and relay the transportation of explosives, the path generation can be similar to that of charging. In the grid map, the position of the current transport robot is used as the new target node, the grid map is updated, and the edge from the intermediate node to the target node is re-determined. When relay is required, the relay path information is generated based on the same A* algorithm. The new transport robot arrives at the designated relay position according to the relay path information to complete the relay of the goods.

[0076] In an embodiment of the present application, information on the distance moved by a transport robot to perform a transport task is obtained; based on the distance information, power consumption information of the transport robot is determined, wherein the power consumption information is used to indicate the amount of power required for the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, a charging path of the transport robot is determined based on position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; the transport robot is controlled to move to the charging device for charging according to the charging path, wherein, during the process of the charging device charging the transport robot, the transport robot is in an unloaded state, thereby achieving the technical effect of improving the safety of charging the transport robot, thereby solving the technical problem of low safety in charging the transport robot.

[0077] In order to facilitate those skilled in the art to better understand the technical solution of the present application, a specific embodiment is now described.

[0078] At present, handling robots are a kind of automated equipment that can be used in industries such as industry, warehousing, and logistics to handle and transport items or goods. Handling robots are usually equipped with various sensors, actuators, and control systems. According to preset tasks and instructions, they can autonomously move, grab, carry, and place items in the working environment and complete corresponding handling tasks. During the operation of the handling robot, different degrees or frequencies of charging operations will be involved depending on the operating range of the handling robot and the intensity of the handling work.

[0079] In the related art, the charging method of the handling robot is usually carried out through a charging pile or a charging station, and the charging process generally sets a minimum power threshold, that is, when the power is lower than a certain threshold, the handling robot goes to the charging pile or charging station to charge by itself. This usually requires the handling robot to be equipped with a positioning system and a navigation system so that the robot can accurately find the charging location. When the intelligent handling robot arrives near the charging pile or charging station, the handling robot will automatically dock with the charging pile and ensure that the charging plug is correctly connected to the charging port of the robot. Some handling robots may use an automatic docking device to ensure that the charging plug is accurately aligned. The intelligent handling robot will start the charging process after connecting to the charging pile. The charging pile usually provides the robot with the required power to ensure that the robot's battery is fully charged. Once the battery of the intelligent handling robot is fully charged, the charging process ends. The intelligent handling robot will disconnect the charging plug, leave the charging pile, and continue to perform the handling task.

[0080] The above method does not present too many problems for handling robots that carry general goods. However, for handling robots that carry specific goods, for example, handling robots that carry flammable and explosive goods, there are greater safety hazards. If charging is only performed by setting the power level below a certain threshold, some handling robots will carry explosives to the charging piles while in the handling state. Due to static electricity or contact discharge of the interface, abnormal discharge sparks are likely to occur during charging, which is an obvious safety hazard for flammable and explosive goods, and there is a technical problem of low safety in charging the handling robot.

[0081] In order to solve the above problems, the present application proposes a charging management method for an intelligent handling robot, which can be applied to the charging management of a handling robot that carries explosives. While ensuring that the handling work is completed efficiently, it can ensure that the handling robot is not in a handling working state during charging, that is, the handling robot is in an unloaded state during the charging process.

[0082] Figure 2 is a flow chart of a charging management method for an intelligent transport robot according to an embodiment of the present application, such as Figure 2 As shown, the process of the charging management method of the intelligent handling robot may include the following steps:

[0083] Step S202, obtaining transport task information, where the transport task information at least includes transport distance information.

[0084] In the above steps, the handling task information is generated or stored in the intelligent warehouse management platform, and each handling robot is connected to the intelligent warehouse management platform. The handling task information generated for each handling task may at least include authorized operator information, handling starting point location information, warehouse number information, explosive item type information, explosive package size information, explosive package weight information, etc. Therefore, when the handling task information is determined, the handling robot can first obtain the handling task information, and further calculate the handling distance information based on the warehouse number information and handling starting point location information in the handling task information.

[0085] Optionally, the handling robot needs to have an operator participate in each handling task. The operator information refers to the identity information of the operator, the number of the authorized warehouse, etc. The explosive size information refers to the length, width, height and volume of the explosive package. When the handling robot is in the handling operation, it is a preset fixed path, and when charging is needed, it is a charging pile from a non-fixed position to a fixed position, and the path needs to be dynamically generated.

[0086] Step S204, determining the single power consumption of the transport task according to the transport distance information and the energy consumption rate of the transport robot.

[0087] In the above steps, there is a correlation between the weight of the transport trolley on the transport robot and the energy consumption, which is the process of calibrating the energy consumption rate. That is, under a fixed warehouse floor environment, a fixed rolling resistance coefficient, the total mass of the transport trolley and the unit load, and a fixed transfer station position to the target position, the energy consumption rate of a single transport is determined: rolling resistance = rolling resistance coefficient × total load mass × gravity acceleration, acceleration force = total load mass × gravity acceleration, energy consumption aluminum = (rolling resistance + acceleration force) × travel speed / operation time.

[0088] Optionally, the power consumption of the handling robot is directly related to the handling distance. In order to avoid potential safety hazards caused by charging, the charging piles in this embodiment are all set at a place outside the minimum safe distance from the explosive warehouse. In order to avoid triggering the charging strategy during transportation, this embodiment evaluates the single power consumption and compares the single power consumption with the remaining power to estimate whether the remaining power is sufficient to complete the next handling. If it cannot be completed, go directly to the charging pile for charging. Among them, when evaluating the single power consumption, the preset energy consumption rate calibrated by the handling robot when it leaves the factory can be relied on for calculation. At this time, the single power consumption can be obtained directly by multiplying the energy consumption rate by the handling distance.

[0089] Optionally, the preset energy consumption rate calibrated by the handling robot when it leaves the factory is usually a calibration value under specific conditions and cannot fully represent the working environment. Therefore, this embodiment recalibrates the energy consumption rate, specifically including: after obtaining the remaining power information, when the remaining power information is greater than the first preset value (for example, 80%), the power consumption of the handling robot when performing a single handling task is monitored in real time through an electric energy meter or a current sensor, and the corresponding power consumption data is recorded, that is, the electric energy consumed by the handling robot at one time when carrying specific goods. The collected power consumption data is analyzed, the actual power consumption of the handling robot during the handling and return journey is calculated, and a calibration data set is generated based on the actual power consumption of multiple handling robots. Based on the calibration data set, a mathematical model of power consumption is established, and the energy consumption rate is recalibrated based on the mathematical model to obtain the actual energy consumption rate.

[0090] The above mathematical model can be a linear model or a nonlinear model, but considering that the actual working conditions include indoors and outdoors, the situation is relatively complicated, so the linear model is generally not accurate. As for the nonlinear model, this embodiment specifically adopts a polynomial model, an exponential model, a logarithmic model or a neural network model. Preferably, this embodiment adopts a neural network model, which can fit the relationship between the robot's energy consumption and the working state through a neural network structure. The construction of the model itself is similar to the existing model structure, including an input layer, a hidden layer, an output layer, connection weights, an activation function and a loss function.

[0091] The input layer receives external input data and passes it to the neural network. Each input node corresponds to a feature or attribute of the input data, and the number of nodes in the input layer depends on the dimension of the input data. The hidden layer is located between the input layer and the output layer, and is the part of the neural network that performs nonlinear transformation and feature extraction. A neural network can contain one or more hidden layers, each of which contains multiple neurons (nodes). The output layer receives the output of the hidden layer and produces the final prediction result or classification result. The number of nodes in the output layer depends on the output type of the model. For example, if it is a regression problem, there is usually only one output node; if it is a classification problem, the number of output nodes is usually equal to the number of categories. Connection weights are parameters in the neural network that are used to adjust the connection strength between neurons. Each connection has a weight value that represents the connection strength between the input node and the output node. These weight values ​​need to be learned and adjusted during the training process. The activation function is a nonlinear transformation function used by each neuron in the hidden layer and the output layer, which converts the weighted sum of the input into the output of the neuron. Common activation functions include Sigmoid, ReLU, Tanh, etc. Different activation functions have different characteristics. The loss function is used to measure the difference between the model's prediction result and the true label. During training, the neural network adjusts the connection weights by minimizing the loss function to improve the model's predictive accuracy.

[0092] After the neural network model is built, the model can be trained using the calibration data set as the training set: the neural network model is initialized using the pre-trained initial connection weights; the calibration data set is used as input data to propagate forward through the neural network, and the output value of each neuron is calculated layer by layer. During the forward propagation process, each neuron calculates the output value through the activation function based on the input data and the connection weight; the output result of the neural network is compared with the true label to calculate the value of the loss function; the connection weights in the neural network are adjusted through the loss function to minimize the loss function value; the connection weights in the neural network are updated using an optimization algorithm (for example, stochastic gradient descent SGD, Adam, Adagrad, etc.); the process of forward propagation, loss function calculation, back propagation, and parameter update is repeated until the stopping condition is reached. The stopping condition can be that the maximum number of iterations is reached and the loss function value converges to a smaller value.

[0093] Step S206, obtain the remaining power information of the transport robot in real time. When the remaining power information is greater than the single power consumption, execute the transport task. When the remaining power information is less than or equal to the single power consumption, obtain the current position information of the transport robot, and generate the charging path information and return path information based on the current position information and the preset charging pile position.

[0094] In the above steps, when the transport robot is carrying, it follows a preset fixed path, and when charging is needed, it goes from a non-fixed position to a fixed charging pile, and the path needs to be dynamically generated. The warehouse in this embodiment is a fixed scene, and generally charging piles are deployed at the four corners of the warehouse, and the positions of the charging piles are also fixed. When generating the charging path and the return path, in fact, only the charging path is generated. The return path is the same as the charging path, but the direction of travel changes.

[0095] Optionally, the step of generating a charging path may be: determining the length and width of the working area of ​​the transport trolley, and determining the coordinate position and area of ​​the static obstacle (stacking area) in the environment; establishing a grid map, dividing the working area into grids, each grid is defined as a grid, and each grid identifies a position and a state, wherein the state refers to occupation or passability. For example, if the grid coincides with the static obstacle, the state is set to occupied or impassable; establishing a graph model of nodes and edges, converting the above grid map into an image, and marking the nodes and edges in the image, wherein the nodes include target nodes and intermediate nodes, the target node refers to a fixed charging pile position, the intermediate node refers to a position point where the route needs to turn at a static obstacle, and the edge refers to a straight line connecting adjacent nodes that does not cross the obstacle grid; calculating the distance between each intermediate node and the target node, and determining the target node and edge closest to each intermediate node; determining the position of the transport trolley based on the positioning, determining the nearest intermediate node based on the position, determining the nearest target node based on the nearest intermediate node, that is, determining the nearest charging pile, and generating a charging path according to the edge between the nearest intermediate node and the target node. Among them, the A* algorithm can be used. The A* algorithm is a widely used heuristic search algorithm suitable for path planning problems. The A* algorithm combines the advantages of the Dijkstra algorithm (i.e. finding the shortest path) and the advantages of heuristic search (i.e. reducing the search space and improving efficiency).

[0096] Step S208, controlling the transport robot to move to the charging pile for charging according to the charging path information, monitoring the charging status of the transport robot in real time, and when charging is completed, controlling the transport robot to return to the transport point according to the return path information.

[0097] In the above steps, the method in this embodiment can ensure that in most cases, the handling robot is not in a handling working state when it needs to be charged. However, due to battery aging factors, the remaining power information of some handling robots may not be accurate, that is, at the beginning of a single handling, the initial assessment can complete a single handling, but the battery decays rapidly during the handling process, so that before reaching the handling end, the battery power reaches the minimum preset value, and the minimum preset value can only support the empty return and system control operation of the handling robot. Therefore, this embodiment considers adding a backup battery to the handling robot to solve the problem, or also considers switching the handling robot to a waiting rescue mode at this time and sending a low-power distress signal and current location information at the same time. The intelligent warehouse management platform dispatches the nearest handling robot to the rescue according to the current location information of the low-power handling robot, and relays the transportation of explosives.

[0098] Optionally, when dispatching the nearest transport robot to go to the rescue and relay the transportation of explosives, the path generation can be similar to that of charging. In the grid map, the position of the current transport robot is used as the new target node, the grid map is updated, and the edge from the intermediate node to the target node is re-determined. When relay is required, the relay path information is generated based on the same A* algorithm. The new transport robot arrives at the designated relay position according to the relay path information to complete the relay of the goods.

[0099] This embodiment avoids the situation of charging during the handling work state to the greatest extent, making the charging of the handling robot more automated and intelligent. According to different working conditions and task information, the charging management plan changes dynamically without human intervention, ensuring the safety and efficiency of the operation.

[0100] It should be noted that, in addition to the neural network model, this embodiment may also adopt an exponential model, which assumes that the energy consumption of the handling robot is exponentially related to the change in the handling weight. The exponential model can be expressed by the following formula:

[0101] E=k×wm

[0102] Among them, E can be used to represent the energy consumption of the robot, k is a constant that can be used to represent the basic energy consumption of the robot or the energy consumption per unit load, w can be used to represent the weight of the transport, and m is an exponential term that can be used to describe the rate at which energy consumption increases with the transport weight. According to this model, when the transport weight w increases, the energy consumption E of the robot will also increase, and the growth rate varies with the value of m. It should be noted that the value of m may vary depending on factors such as the type of transport robot, the working environment, and the characteristics of the task. In general, m can be determined through artificial experimental tests to most accurately reflect the relationship between the energy consumption of the transport robot and the transport weight.

[0103] In an embodiment of the present application, information on the distance moved by a transport robot to perform a transport task is obtained; based on the distance information, power consumption information of the transport robot is determined, wherein the power consumption information is used to indicate the amount of power required for the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, a charging path of the transport robot is determined based on position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; the transport robot is controlled to move to the charging device for charging according to the charging path, wherein, during the process of the charging device charging the transport robot, the transport robot is in an unloaded state, thereby achieving the technical effect of improving the safety of charging the transport robot, thereby solving the technical problem of low safety in charging the transport robot.

[0104] The embodiment of the present application also provides a charging device for a handling robot. It should be noted that the charging device for a handling robot of the embodiment can be used to implement the charging method for a handling robot of the embodiment of the present invention.

[0105] Figure 3 is a schematic diagram of the structure of a charging device for a transport robot according to an embodiment of the present application, such as Figure 3 As shown, the charging device 300 of the transport robot may include: an acquisition unit 302 , a first determination unit 304 , a second determination unit 306 and a charging unit 308 .

[0106] The acquisition unit 302 is used to acquire the distance information moved by the transport robot to perform the transport task.

[0107] The first determining unit 304 is used to determine the power consumption information of the transport robot based on the distance information, wherein the power consumption information is used to indicate the power consumed by the transport robot to perform the transport task.

[0108] The second determination unit 306 is used to determine the charging path of the transport robot in response to the power information of the transport robot being less than or equal to the power consumption information and based on the position information of the transport robot, wherein the power information is used to indicate the power allowed to be consumed by the transport robot and a charging device is deployed at the end of the charging path.

[0109] The charging unit 308 is used to control the transport robot to move to the charging device for charging according to the charging path, wherein the transport robot is in an unloaded state during the process of the charging device charging the transport robot.

[0110] Optionally, the second determination unit 306 includes: a first determination module, used to determine the passage area of ​​the transport robot based on the size information of the transport robot and the environmental information of the transport robot; a second determination module, used to determine, based on the passage area, multiple passage positions through which the transport robot will perform the transport task; and a third determination module, used to determine the charging path based on the position information and multiple passage positions.

[0111] Optionally, the third determination module includes: a first determination submodule, used to determine the target passing position from multiple passing positions based on the position information; a second determination submodule, used to determine the charging position of the charging device based on the target passing position; and a generation submodule, used to generate a charging path based on the target passing position and the charging position of the charging device.

[0112] Optionally, the device includes: an acquisition unit, used to acquire the rolling resistance and acceleration force of the transport robot to perform a transport task; and a third determination unit, used to determine the energy consumption rate of the transport robot based on the rolling resistance and the acceleration force.

[0113] Optionally, the third determination unit includes: a fourth determination module, used to determine the power consumption information of the transport robot based on the distance information and the energy consumption rate.

[0114] Optionally, the fourth determination module includes: a calibration submodule, used to call the neural network model, calibrate the energy consumption rate, and obtain a target energy consumption rate, wherein the neural network model is obtained based on energy consumption rate sample training; a third determination submodule, used to determine the power consumption information of the transport robot based on the distance information and the target energy consumption rate.

[0115] Optionally, after controlling the transport robot to move to the charging device for charging according to the charging path, the device also includes: a monitoring unit for monitoring the charging status of the transport robot; a first control unit for controlling the transport robot to move to a target area according to a return path corresponding to the charging path in response to the charging status being a charging completion state, wherein the target area is located at the starting point of the charging path, and the target area is located at the end point of the return path.

[0116] Optionally, the device further includes: a second control unit, configured to control the transport robot to perform a transport task in response to the power information of the transport robot being greater than the power consumption information.

[0117] Optionally, the device also includes: a first charging unit, used to charge the transport robot using a backup battery in response to the power information being less than or equal to the power consumption information and the transport robot being in a no-load state during the process of controlling the transport robot to perform a transport task.

[0118] In the device, the information of the distance moved by the transport robot to perform the transport task is obtained by the acquisition unit 302. The power consumption information of the transport robot is determined based on the distance information by the first determination unit 304, wherein the power consumption information is used to indicate the amount of power required to be consumed by the transport robot to perform the transport task. In response to the power information of the transport robot being less than or equal to the power consumption information, the second determination unit 306 determines the charging path of the transport robot based on the position information of the transport robot in response to the power information of the transport robot being less than or equal to the power consumption information, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path. The charging unit 308 controls the transport robot to move to the charging device for charging according to the charging path, wherein, during the process of the charging device charging the transport robot, the transport robot is in an unloaded state, thereby achieving the technical effect of improving the safety of charging the transport robot, and thus solving the technical problem of low safety of charging the transport robot.

[0119] According to another aspect of an embodiment of the present application, a non-volatile storage medium is further provided, the non-volatile storage medium including a stored program, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute any one of the charging methods for the transport robot.

[0120] Specifically, the above storage medium is used to store program instructions for the following functions to implement the following functions:

[0121] Obtain information on the distance that the transport robot has moved to perform a transport task; based on the distance information, determine power consumption information of the transport robot, wherein the power consumption information is used to indicate the amount of power required for the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, determine a charging path for the transport robot based on position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; control the transport robot to move to the charging device for charging according to the charging path, wherein the transport robot is in a no-load state while the charging device is charging the transport robot.

[0122] Optionally, in this embodiment, the above-mentioned storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above-mentioned contents. More specific examples of the above-mentioned storage medium may include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above-mentioned contents.

[0123] According to another aspect of an embodiment of the present invention, a processor is further provided, and the processor is used to run a program, wherein the charging method for the transport robot in the embodiment of the present invention is executed when the program is run.

[0124] Optionally, the following steps may be implemented when the program is executed at runtime:

[0125] Obtain information on the distance that the transport robot has moved to perform a transport task; based on the distance information, determine power consumption information of the transport robot, wherein the power consumption information is used to indicate the amount of power required for the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, determine a charging path for the transport robot based on position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; control the transport robot to move to the charging device for charging according to the charging path, wherein the transport robot is in a no-load state while the charging device is charging the transport robot.

[0126] In an exemplary embodiment of the present application, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, it implements any of the above-mentioned methods for charging a transport robot.

[0127] Optionally, the computer program may implement the following steps when executed by a processor:

[0128] Obtain information on the distance that the transport robot has moved to perform a transport task; based on the distance information, determine power consumption information of the transport robot, wherein the power consumption information is used to indicate the amount of power required for the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, determine a charging path for the transport robot based on position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; control the transport robot to move to the charging device for charging according to the charging path, wherein the transport robot is in a no-load state while the charging device is charging the transport robot.

[0129] In an exemplary embodiment of the present application, a computer program product is also provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and the computer program is configured to execute any of the above-mentioned methods for charging a transport robot when running.

[0130] Optionally, the computer program may implement the following steps when executed by a processor:

[0131] Obtain information on the distance that the transport robot has moved to perform a transport task; based on the distance information, determine power consumption information of the transport robot, wherein the power consumption information is used to indicate the amount of power required for the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, determine a charging path for the transport robot based on position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; control the transport robot to move to the charging device for charging according to the charging path, wherein the transport robot is in a no-load state while the charging device is charging the transport robot.

[0132] In an exemplary embodiment of the present application, a computer program is further provided. The computer program is configured to execute the steps in any of the above method embodiments when running.

[0133] Optionally, the computer program may implement the following steps when executed by a processor:

[0134] Obtain information on the distance that the transport robot has moved to perform a transport task; based on the distance information, determine power consumption information of the transport robot, wherein the power consumption information is used to indicate the amount of power required for the transport robot to perform the transport task; in response to the power information of the transport robot being less than or equal to the power consumption information, determine a charging path for the transport robot based on position information of the transport robot, wherein the power information is used to indicate the amount of power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; control the transport robot to move to the charging device for charging according to the charging path, wherein the transport robot is in a no-load state while the charging device is charging the transport robot.

[0135] According to an embodiment of the present application, an electronic device is provided, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any one of the above-mentioned charging methods for the transport robot.

[0136] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0137] Figure 4is a schematic block diagram of an electronic device according to an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0138] like Figure 4 As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0139] A number of components in the device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0140] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 401 performs the various methods and processes described above, such as the charging method of the handling robot. For example, in some embodiments, the charging method of the handling robot may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the charging method of the handling robot described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the charging method of the handling robot in any other appropriate manner (e.g., by means of firmware).

[0141] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0142] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0143] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0144] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0145] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0146] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0147] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0148] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0149] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, 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, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0150] The units described 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 units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0151] 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.

[0152] If the 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 storage medium. Based on this understanding, the technical solution of the present application, in essence, 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 storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0153] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A charging method for a handling robot, characterized in that: include: Obtaining information on the distance that the transport robot has moved to perform a transport task; Based on the distance information, determining the power consumption information of the transport robot, wherein the power consumption information is used to indicate the power consumed by the transport robot to perform the transport task; In response to the power information of the transport robot being less than or equal to the power consumption information, a charging path of the transport robot is determined based on the position information of the transport robot, wherein the power information is used to indicate the power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; The transport robot is controlled to move to the charging device for charging according to the charging path, wherein the transport robot is in an unloaded state during the process of the charging device charging the transport robot.

2. The method according to claim 1, characterized in that Determining a charging path of the transport robot based on the position information of the transport robot includes: Determining a passage area of ​​the transport robot based on size information of the transport robot and environmental information of the transport robot; Based on the passage area, determining a plurality of passage positions through which the transport robot will pass to perform the transport task; The charging path is determined based on the position information and the plurality of passing locations.

3. The method according to claim 2, characterized in that Determining the charging path based on the location information and the plurality of passing locations includes: Based on the position information, determining a target passing position from the plurality of passing positions; Determining a charging position of the charging device based on the target passing position; The charging path is generated based on the target passing position and the charging position of the charging device.

4. The method according to claim 1, characterized in that: The method comprises: Obtaining the rolling resistance and acceleration force of the transport robot to perform the transport task; An energy consumption rate of the transport robot is determined based on the rolling resistance and the acceleration force.

5. The method according to claim 4, characterized in that Based on the distance information, determining the power consumption information of the transport robot includes: Based on the distance information and the energy consumption rate, the power consumption information of the transport robot is determined.

6. The method according to claim 5, characterized in that Determining the power consumption information of the transport robot based on the distance information and the energy consumption rate includes: Calling a neural network model to calibrate the energy consumption rate to obtain a target energy consumption rate, wherein the neural network model is trained based on energy consumption rate samples; Based on the distance information and the target energy consumption rate, the power consumption information of the transport robot is determined.

7. The method according to claim 1, characterized in that After controlling the transport robot to move to the charging device for charging according to the charging path, the method further includes: Monitoring the charging status of the handling robot; In response to the charging state being a charging completion state, the transport robot is controlled to move to a target area according to a return path corresponding to the charging path, wherein the target area is located at a starting point of the charging path and an end point of the return path.

8. The method according to claim 1, characterized in that The method further comprises: In response to the power information of the transport robot being greater than the power consumption information, the transport robot is controlled to perform the transport task.

9. The method according to claim 8, characterized in that The method further comprises: During the process of controlling the transport robot to perform the transport task, in response to the power information being less than or equal to the power consumption information and the transport robot being in the no-load state, the transport robot is charged by using a backup battery.

10. A charging device for a handling robot, characterized in that: include: An acquisition unit, used for acquiring information about the distance moved by the transport robot to perform a transport task; A first determining unit, configured to determine power consumption information of the transport robot based on the distance information, wherein the power consumption information is used to indicate the power consumed by the transport robot to perform the transport task; a second determining unit, configured to determine, in response to the power information of the transport robot being less than or equal to the power consumption information, a charging path of the transport robot based on the position information of the transport robot, wherein the power information is used to indicate the power allowed to be consumed by the transport robot, and a charging device is deployed at the end of the charging path; The charging unit is used to control the transport robot to move to the charging device for charging according to the charging path, wherein the transport robot is in an unloaded state during the process of the charging device charging the transport robot.

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