A method, apparatus and robotic system for robot charging

Abstract

This application discloses a method, apparatus, and robot system for charging robots, relating to the field of photovoltaic charging control technology. The method includes: identifying robots in a target area where the light intensity is greater than a preset intensity as target robots; determining requesting robots and election request information based on the maximum power point tracking (MPPT) scan results of the target robots; electing a master node based on the election request information and the MPPT parameters of the responding robots; synchronizing the MPPT parameters of the master node to slave nodes at a preset frequency, enabling the slave nodes to charge according to the parameters of the master node. This application, through a master node election and parameter sharing mechanism, avoids repeated MPPT scans by each robot, reduces system energy consumption and computational redundancy, effectively improves the charging efficiency of cluster robots, and is suitable for high-efficiency charging scenarios for large-scale photovoltaic robots.

Description

Technical Field

[0001] This application relates to the field of solar charging technology, and in particular to a method, apparatus and robot system for charging a robot. Background Technology

[0002] Robots equipped with photovoltaic charging capabilities can absorb solar energy through their own photovoltaic modules and use maximum power point tracking (MPPT) scanning to charge their built-in batteries for continuous operation.

[0003] In existing technologies, each robot independently executes the MPPT scanning process, continuously and in real-time scanning the voltage-current curve of its own photovoltaic module to determine the maximum charging parameters. However, each MPPT scanning process takes a certain amount of time, and in large-scale robot scenarios, a large number of redundant scanning operations are generated, resulting in a longer overall charging time and low charging efficiency. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a method, apparatus, and robot system for charging robots, enabling multiple robots to synchronize their maximum power point (MPP) parameters and meeting the demand for efficient charging in large-scale robot scenarios.

[0005] This application discloses a method for charging a robot, the method comprising: The requesting robot and the campaign request information are identified among the target robots; the target robot is the robot in the target area where the light intensity is greater than a preset intensity; the requesting robot is the robot among the target robots that first completes the maximum power point tracking scan and obtains the maximum power point (MPP) parameters; the campaign request information includes the MPP parameters of the requesting robot; Based on the election request information and the MPP parameters of the responding robot, a master node is elected; the responding robot is one of the target robots excluding the requesting robot; the master node is one of the target robots. The master MPP parameters are transmitted to the slave node at a preset frequency, so that the slave node charges based on the master MPP parameters; the master MPP parameters are the MPP parameters of the master node; the slave node is a robot in the target robot other than the master node.

[0006] Optionally, the election of a master node based on the election request information and the MPP parameters of the response robot includes: The requesting robot transmits the campaign request information to each of the responding robots; The requesting robot and the responding robot compete for the master node among the target robots based on their respective MPP parameters.

[0007] Optionally, the requesting robot and the responding robot compete for the master node among the target robots based on their respective MPP parameters, including: Add the requesting robot to the election set; The response robot calculates its own power based on its own MPP parameters and calculates its campaign power based on the campaign request information. If its own power is less than or equal to the election power, the responding robot will not participate in the election; If its own power is greater than the election power, the responding robot enters the election set; Obtain the master node from the election set.

[0008] Optionally, obtaining the master node from the election set includes: The robots in the campaign set send their own MPP parameters to the platform; The robot corresponding to the MPP parameter with the highest power among the received MPP parameters obtained by the platform is the master node.

[0009] Optionally, obtaining the master node from the election set includes: The first robot, which is the first in the election set, transmits its first MPP parameters to the second robot; the second robot is any robot in the election set other than the first robot. If the second power is less than or equal to the first power, the second robot is removed from the election set; the second power is calculated from the second robot's own second MPP parameter; the first power is calculated from the first MPP parameter; When the second power is greater than the first power, the second robot remains in the election set; The robots in the election set repeatedly transmit MPP parameters and compare power until the number of robots in the election set is one.

[0010] Optionally, transmitting the master MPP parameters to the slave node at a preset frequency includes: The platform sends election completion information to the master node; In response to the election completion information, the master node transmits the master MPP parameters to the slave node at the preset frequency.

[0011] Optionally, after transmitting the master MPP parameters to the slave node at a preset frequency, the method further includes: If the deviation between the slave power and the master power is greater than a preset value, the slave node corresponding to the slave power is controlled to charge based on the slave MPP parameters; the slave power is calculated from the slave MPP parameters; the master power is calculated from the master MPP parameters; the slave MPP parameters are the MPP parameters of the slave node.

[0012] Optionally, after the slave node is charged based on the master MPP parameters, the method further includes: The first information of the target area and the second information of the adjacent target areas are compared at a globally preset frequency; the first information includes the main MPP parameter or average light intensity of the target area, and the second information includes the main MPP parameter or average light intensity of the adjacent target areas. If the first information and the second information are of the same type and their difference is less than a preset global difference, the first information and the second information are synchronized into synchronization information; the synchronization information is the information with the larger value between the first information and the second information.

[0013] Optionally, after the slave node is charged based on the master MPP parameters, the method further includes: The status of the master node in the target area is acquired at a preset monitoring frequency; If the state is not obtained for a preset number of consecutive times, a new master node will be elected within the target area, or the master MPP parameters of the adjacent target area will be called.

[0014] Optionally, before transmitting the master MPP parameters to the slave node at a preset frequency, the method further includes: Obtain the original master MPP parameters; the original master MPP parameters are obtained by the master node performing an MPPT scan. Once the recommended value is obtained, the processing parameters are calculated based on the original master MPP parameters and the recommended value; the recommended value is obtained at a preset frequency and is related to the light intensity and temperature. The parameter with the larger value among the processing parameters and the original master MPP parameters is determined as the master MPP parameter.

[0015] Optionally, transmitting the master MPP parameters to the slave node at a preset frequency includes: The master MPP parameters are broadcast via LoRa communication; The slave nodes within a preset distance from the master node simultaneously receive the master MPP parameters via LoRa and Bluetooth communication.

[0016] Based on the above-mentioned robot charging method, this application also discloses a robot charging device, including: a determining unit, a candidate unit, and a transmission unit; The determining unit is used to determine the requesting robot and the election request information among the target robots; the target robot is the robot in the target area where the light intensity is greater than a preset intensity; the requesting robot is the robot among the target robots that first completes the maximum power point tracking scan and obtains the maximum power point (MPP) parameters; the election request information includes the MPP parameters of the requesting robot; The election unit is used to elect a master node based on the election request information and the MPP parameters of the responding robot; the responding robot is a robot among the target robots excluding the requesting robot; the master node is one of the target robots. The transmission unit is used to transmit the master MPP parameters to the slave node at a preset frequency, so that the slave node can charge based on the master MPP parameters; the master MPP parameters are the MPP parameters of the master node; the slave node is a robot other than the master node in the target robot.

[0017] Optionally, the campaign unit includes: The campaign transmission subunit is used by the requesting robot to transmit the campaign request information to each of the responding robots; The election response subunit is used for the requesting robot and the responding robot to compete for the master node in the target robot according to their respective MPP parameters.

[0018] Optionally, the campaign response subunit includes: Add a sub-unit to the set, used to add the requesting robot to the election set; The power calculation subunit is used by the response robot to calculate its own power based on its own MPP parameters and to calculate the campaign power based on the campaign request information. The non-participation in the election subunit is used so that the response robot does not participate in the election when its own power is less than or equal to the election power; The participating election subunit is used so that, when its own power is greater than the election power, the responding robot enters the election set; The master node election subunit is used to obtain the master node from the election set.

[0019] Optionally, the master node election subunit includes: The platform receiving subunit is used for robots in the election set to send their own MPP parameters to the platform. The platform election subunit is used to select the robot corresponding to the MPP parameter with the highest power among the received MPP parameters as the master node.

[0020] Optionally, the master node election subunit includes: The robot receiving subunit is used for the first robot, which is the first in the candidate set, to transmit its first MPP parameters to the second robot; the second robot is a robot in the candidate set other than the first robot. The robot removal subunit is used to remove the second robot from the campaign set when the second power is less than or equal to the first power; the second power is calculated from the second robot's own second MPP parameter; the first power is calculated from the first MPP parameter; A robot holding subunit is configured to keep the second robot in the campaign set when the second power is greater than the first power; The robot election subunit is used for repeated MPP parameter transmission and power comparison among the robots in the election set until the number of robots in the election set is one.

[0021] Optionally, the transmission unit includes: The master node notification subunit is used by the platform to send election completion information to the master node. The master node transmission subunit is used by the master node in response to the election completion information to transmit the master MPP parameters to the slave node at the preset frequency.

[0022] Optionally, the device further includes: A deviation control unit is used to control the slave node corresponding to the slave power to charge based on the slave MPP parameters when the deviation between the slave power and the master power is greater than a preset value; the slave power is calculated from the slave MPP parameters; the master power is calculated from the master MPP parameters; and the slave MPP parameters are the MPP parameters of the slave node.

[0023] Optionally, the device further includes: A global parameter comparison unit is used to compare first information of the target area with second information of adjacent target areas at a global preset frequency; the first information includes the main MPP parameter or average light intensity of the target area, and the second information includes the main MPP parameter or average light intensity of the adjacent target areas. A synchronization unit is used to synchronize the first information and the second information into synchronization information when the first information and the second information are of the same type and the difference between them is less than a preset global difference; the synchronization information is the information with the larger value between the first information and the second information.

[0024] Optionally, the device further includes: The status monitoring unit is used to acquire the status of the master node in the target area at a preset monitoring frequency; The re-election unit is used to elect a new master node in the target area or call the master MPP parameters of an adjacent target area if the state is not obtained for a preset number of consecutive times.

[0025] Optionally, the device further includes: The raw parameter acquisition unit is used to acquire the raw master MPP parameters; the raw master MPP parameters are obtained by the master node performing an MPPT scan. The parameter calculation unit is used to calculate the processing parameters based on the original master MPP parameters and the recommended values ​​when the recommended values ​​are obtained; the recommended values ​​are obtained at a preset frequency and are related to the light intensity and temperature. The parameter determination unit is used to determine the parameter with the larger value among the processing parameters and the original master MPP parameters as the master MPP parameter.

[0026] Optionally, the transmission unit includes: The broadcast subunit is used to broadcast the main MPP parameters via LoRa communication; The receiving subunit is used to control the slave nodes within a preset distance from the master node to simultaneously receive the master MPP parameters via LoRa communication and Bluetooth communication.

[0027] Based on the above-described method for charging a robot, this application also discloses a robot system, including a processor and a memory, wherein the memory is used to store a computer program, the computer program including instructions, and the instructions are executed by the processor to implement the above-described method.

[0028] This application discloses a method, apparatus, and robot system for charging robots. The method involves identifying robots in a target area where the light intensity is greater than a preset intensity as target robots, the robot among the target robots that first completes an MPPT scan and obtains MPP parameters as a requesting robot, and the other target robots as responding robots. Election request information, including the MPP parameters of the requesting robots, is also obtained. Subsequently, based on the election request information and the MPP parameters of the responding robots, a master robot is elected from among the target robots, and the remaining robots become slave nodes. The master node's master MPP parameters are transmitted to the slave nodes at a preset frequency, enabling the slave nodes to charge based on the master MPP parameters. By using master node election and MPP parameter synchronization, each robot does not need to perform independent MPPT scans in real time, reducing redundant scanning time, improving charging efficiency, and meeting the demand for high-efficiency charging in large-scale robot scenarios. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0030] Figure 1 This is a flowchart illustrating a method for charging a robot as disclosed in an embodiment of this application; Figure 2 A schematic flowchart illustrating another method for charging a robot disclosed in an embodiment of this application; Figure 3 This is a schematic diagram of a robot charging device disclosed in an embodiment of this application. Detailed Implementation

[0031] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0032] Example 1: This application discloses a method for charging a robot.

[0033] For details, please refer to Figure 1 The robot charging method disclosed in this embodiment includes the following steps: Step 101: Identify the requesting robot and campaign request information in the target robot.

[0034] In this embodiment, the robot is equipped with a photovoltaic module, an MPPT module, and a communication module. The photovoltaic module absorbs solar energy and outputs direct current, while the MPPT module performs MPPT scanning and outputs MPP parameters (including the maximum charging voltage Vmpp and the maximum charging current Impp). The communication module may specifically include wireless communication modules such as LoRa and Bluetooth modules for information transmission between robots and between the robot and the management platform. Furthermore, the robot is also equipped with a light sensor for collecting light intensity, as well as basic components such as a battery and a control unit.

[0035] In this embodiment, a communication coordination unit can be set up in the global central area, which may specifically include a LoRa gateway, Bluetooth repeater, etc. Its functions include forwarding information from each robot to the management platform, monitoring the master node status, and allocating communication time slots according to the robot scale to avoid channel congestion. The association platform can be used to store information such as MPP parameters and includes a machine learning algorithm (such as a random forest) module to analyze the correlation between light intensity, temperature, and MPP parameters, in order to generate processing parameters for optimizing the original MPP parameters.

[0036] In the method of this embodiment, multiple robots can first be divided into different areas. As one feasible solution, if the robots have group number attributes, robots with the same or related group numbers can be grouped together (this group constitutes one area). Another feasible solution is to divide the areas based on the angle of the robot's photovoltaic module, such as assigning robots with a 15° photovoltaic module angle to the first area, robots with a 20° photovoltaic module angle to the second area, and so on. In this way, all the robots in the field are divided into multiple areas, with at least one robot in each area. Furthermore, the area identifiers of the divided areas can be remotely sent to the robots for storage, facilitating the viewing and management of the areas to which the robots belong. For special needs, specific robots can also be assigned to a single area; this will not be elaborated upon further, as long as the robot area division is achieved.

[0037] In this embodiment, after each robot in each area is started or reset, it collects the current light intensity through its own light sensor and performs an independent MPPT scan through its own MPPT module. Within a certain target area, the light intensity is greater than a preset intensity (e.g., 200W / m²). 2Robots within the target area are designated as target robots. These target robots can proceed with the subsequent master node election and MPP parameter synchronization steps. Other robots in the target area, excluding the target robots, may be in a low-light environment due to insufficient illumination and therefore will not proceed with these steps; they will simply charge according to their own MPP parameters. The preset intensity can be data pre-distributed by the platform and stored locally on the robot, or data obtained from the platform upon robot startup. No specific restrictions are placed on the storage or retrieval method of the preset intensity; the robot only needs to obtain it.

[0038] In the method of this embodiment, a target robot has not received any campaign request information from other robots until it completes the MPPT scan and obtains the MPP parameters. This indicates that the target robot is the first target robot to obtain the MPP parameters. Therefore, the target robot, as the requesting robot, generates campaign request information containing its own MPP parameters and transmits it to other robots.

[0039] For example, after all robots in the target area collect the light intensity, they compare it with a preset intensity to determine if they are the target robot. If they are the target robot, they continuously check whether they have received information from other robots. If they are not the target robot, they do not proceed with the subsequent steps. Subsequently, if target robot #1 has not received any election request information after obtaining the MPP parameters, it generates election request information as the requesting robot and transmits it to other robots. If target robot #1 receives election request information during the MPPT scan, it will not generate election request information.

[0040] In the method of this embodiment, as an feasible solution, the election request information may also include the light intensity of the requesting robot, so as to assist the MPP parameter in realizing the master node election when the MPP parameter is unavailable (such as invalid, non-existent, etc.) or when the light intensity needs to be used as an election indicator.

[0041] Step 102: Based on the election request information and the MPP parameters of the responding robot, a master node is elected.

[0042] In this embodiment, the requesting robot can broadcast election request information within the target area via a wireless communication module. All other robots within the target area, except the requesting robot, can receive this election request information. Non-target robots can ignore the election request information, while the remaining target robots, acting as responding robots, receive and parse the election request information to obtain the contained MPP parameters, and then perform subsequent master node election steps based on these MPP parameters.

[0043] In this embodiment, each responding robot calculates its own power based on its own MPP parameters and its campaign power based on the MPP parameters in the campaign request information. Response robots with a power less than or equal to their campaign power do not participate in the campaign, while response robots with a power greater than their campaign power participate in the campaign and enter the campaign set. This embodiment constructs a conceptual campaign set for these participating robots. This campaign set is not necessarily an actual entity (such as a list or directory), but rather a collective term for all participating robots.

[0044] In this embodiment, as an feasible approach, robots in the election set can send their own MPP parameters to the platform. After receiving the MPP parameters, the platform calculates the power and selects the MPP parameter with the highest calculated power, choosing the robot corresponding to this MPP parameter as the master node. For example, robot a in the election set sends its MPP parameter a... Sending the MPP parameters to the platform, robot b will... Send to the platform. The platform calculates a respectively. power a and b power b Comparison yields b Greater than a Therefore, robot b is selected as the master node. In this step, if there are multiple robots with equal power in the candidate set, the platform can have these robots upload their light intensity for a secondary comparison. If the secondary comparison still finds robots with equal light intensity, the platform can select the robot with the earliest number among these robots as the master node.

[0045] In this embodiment, the robot's number can be a number or a code containing text, and it has a sequential order. This order can be set manually or sorted according to the robot's production time, etc. The order or specific content of the robot numbers is not limited here; it only needs to be able to distinguish different robots and represent a general sequential order. For example, if robot 001 and robot 002 have equal power and light intensity, the platform can select robot 001, which has the earlier number, as the master node. Similarly, if robot c and robot f have equal power and light intensity, the platform can select robot c, which has the earlier number, as the master node. It should be noted that there is only one master node, and it is one of the target robots.

[0046] Considering the possibility of network issues preventing communication between the robots and the platform, as an alternative solution, the first robot in the election set can transmit its first MPP parameter to the second robot in the election set (excluding itself). The second robot calculates its second power based on its second MPP parameter and its first power based on its first MPP parameter. If the second power is less than or equal to the first power, the second robot is removed from the election set. If the second power is greater than the first power, the second robot remains in the election set for the next round of election. In the next round of election, the robots in the election set repeat the process of the first robot sending its MPP parameter and comparing its power with other robots until only one robot remains in the election set; this robot becomes the master node.

[0047] In this embodiment, as an feasible solution, when the MPP parameter in the election request information is unavailable and the election request information includes light intensity, each responding robot can also perform the aforementioned master node election steps based on the light intensity. Specifically, responding robots whose own light intensity is less than or equal to the light intensity in the election request information do not participate in the election, while responding robots whose own light intensity is greater than the light intensity in the election request information participate in the election and enter the election set. Subsequently, they also follow the method of election based on MPP parameters, and conduct election based on light intensity to obtain the master node.

[0048] As an alternative approach, when the election request information includes MPP parameters and light intensity, each responding robot can perform a weighted calculation of the MPP parameters and light intensity based on preset weights to obtain a comparison value. The election of the master node is then based on this combined comparison value. For example, a responding robot whose comparison value is less than or equal to the comparison value calculated from the election request information does not participate in the election; a responding robot whose comparison value is greater than the comparison value calculated from the election request information participates in the election and enters the election set. Subsequent elections are still conducted based on the comparison value, following the same method as the MPP parameter-based election, to determine the master node.

[0049] Step 103: Transmit the master MPP parameters to the slave node at a preset frequency, so that the slave node can charge based on the master MPP parameters.

[0050] In the method of this embodiment, if the platform elects a master node, the platform can send an election completion message to the master node, and the robots other than the master node among the target robots are slave nodes. In response to the election completion message, the master node transmits the master node's main MPP parameters to the slave nodes within the target area at a preset frequency (e.g., 5~30s, which can be dynamically adjusted according to the frequency of regional light fluctuations).

[0051] As a feasible approach, the master node can first obtain the original master MPP parameters after performing an MPPT scan. These original master MPP parameters, along with light intensity and temperature, are then calculated using a machine learning algorithm to analyze the correlation between light intensity, temperature, and the original master MPP parameters, thus obtaining processing parameters. Subsequently, the parameter with the larger value among these processing parameters and the original master MPP parameters is identified as the master MPP parameter, thereby further determining the optimality of the master MPP parameters.

[0052] In this embodiment, when there is an anomaly in the area where a slave node is located (such as shadow occlusion), the slave MPP parameters will differ significantly from the master MPP parameters. In this case, the slave node can be flagged and reported to the platform for subsequent investigation. Specifically, each slave node can simultaneously receive the master MPP parameters and perform a brief verification scan (a shortened form of the MPPT scan, taking ≤50ms, much shorter than a full MPPT scan) to obtain its own slave MPP parameters. Each slave node calculates the master power and slave power based on the master and slave MPP parameters, and further calculates the deviation between the master power and slave power. This deviation can be in integer, fractional, or percentage form, i.e., the deviation rate. The specific form of the deviation is not limited here; it only needs to represent the difference between the master power and slave power. Taking the deviation rate as an example, the formula for calculating the deviation rate is as follows: (1) (2) (3) In the formula, Vmpp main The maximum charging voltage, Vmpp, is a key MPP parameter. slave The maximum charging voltage from the MPP parameters, Imppp main The maximum charging current in the main MPP parameters, Imppp slave P is the maximum charging current from the MPP parameters. main Main power, P slave Let δ be the power, and δ be the deviation rate. In this embodiment, when the deviation is less than or equal to a preset value, the master MPP parameters are used to charge the slave node itself. Taking the aforementioned deviation rate as an example, if δ≤5%, the master MPP parameters are deemed valid, and each slave node adjusts its charging circuit based on the master MPP parameters, that is, adjusts Vmpp. slave For Vmpp main Adjust Imppp slave For Imppp main No separate scan is needed. The 5% figure is just an example and can be set according to actual needs; no specific limit is set here.

[0053] In the method of this embodiment, if the deviation is greater than a preset value, the slave node corresponding to the MPP parameter can be marked as an abnormal node, and the abnormal node can be controlled to charge based on the MPP parameter, or not to charge the abnormal node. Taking the above deviation rate as an example, if δ > 5%, the slave node can report abnormal information in the area and charge using its own MPP parameter. Subsequently, the management platform can mark the slave node as an abnormal node, verify whether there is local shadow in the environment where the abnormal node is located, or verify whether the area division is unreasonable, and perform optimization processing such as checking for obstructions and fine-tuning the area boundary based on the verification results.

[0054] In the method of this embodiment, there are usually multiple target regions. Taking the first target region and the second target region in the global context as an example, the first target region has its own master MPP parameters, and the second target region also has its own master MPP parameters.

[0055] As a feasible solution, a first piece of information containing the main MPP parameters of the first target region and a second piece of information containing the main MPP parameters of the second target region can be compared at a globally preset frequency. If the difference between the first and second pieces of information, i.e., the difference between the two main MPP parameters, is less than a preset global difference, the first and second pieces of information can be synchronized. The synchronized information is the one with the larger value between the first and second pieces of information, i.e., the superior main MPP parameter. Conversely, if the difference between the first and second pieces of information is greater than or equal to the preset global difference, each target region can use its own main MPP parameters.

[0056] As a feasible approach, the first and second information can also include the average illumination intensity of their target areas. Therefore, the difference between the first and second information can also include the difference between the two average illumination intensities. When the difference between the two average illumination intensities is less than a preset global difference, the first and second information are synchronized. For example, if the difference in average illumination intensity between the first and second target areas is ≤3%, then the first and second information are synchronized.

[0057] As another feasible solution, when the first information and the second information include both the main MPP parameters and the average illuminance, the difference between the two main MPP parameters and the difference between the two average illuminance can be calculated first, and then the two differences can be weighted. If the weighted calculation result is ≤3%, then the first information and the second information can be synchronized into synchronized information.

[0058] Furthermore, based on the calculation of the difference between the first and second information, it can be further determined whether the first and second information need to be synchronized by the difference in the component orientation angles of the two target areas. For example, if the difference between the first and second information is ≤3%, and the difference in the component orientation angles of the two target areas is ≤5°, then the first and second information should be synchronized. Correspondingly, there are also ways to make judgments using other indicators, which will not be elaborated on here. It is sufficient to determine whether the difference in robot charging parameters and light intensity between the two target areas is too large. Similarly, the 3% and 5° mentioned are just examples and can be set according to actual needs. No specific limitation is made on these values ​​here.

[0059] In this embodiment, the management platform can preset a monitoring frequency to obtain the status of the master node in the first target area. If the status is not obtained for a preset number of consecutive times (e.g., 3 times), a new master node is elected in the first target area. Further, if a master node has not been elected in the first target area within a preset time (e.g., 30 seconds), the master MPP parameters of the second target area are temporarily invoked. After a master node is elected in the first target area, the master MPP parameters of the first target area itself are then used. The difference between the light intensity of the second target area and the light intensity of the first target area must be less than a preset value (e.g., 5%).

[0060] In this embodiment, the wireless communication method can be LoRa communication, such as broadcasting the master MPP parameters via a LoRa repeater. Alternatively, the wireless communication can combine LoRa and Bluetooth communication; for example, slave nodes within a preset distance of the master node can simultaneously receive the master MPP parameters via both LoRa and Bluetooth communication to achieve rapid information transmission between two nodes at close range. Furthermore, data transmission in wireless communication can be encrypted, and the encryption key can be updated periodically, with the key distribution record stored by the global communication gateway. Similarly, the communication method in this embodiment is merely an example; other low-power wide-area network (LPWAN) wireless communication technologies can also achieve data communication such as master MPP parameter transmission, and no specific limitations are imposed on the communication method here.

[0061] The method described in this embodiment, through master node election and parameter synchronization, eliminates the need for each robot to perform independent MPPT scans in real time. This reduces the time spent by each robot performing independent scans, improves charging efficiency, and significantly shortens the time it takes for the entire robot to reach a stable charging state. Furthermore, the use of light intensity-assisted verification and abnormal slave node marking enhances the anti-interference capability of the global robot charging efficiency, meeting the demand for high-efficiency charging in large-scale robot scenarios.

[0062] Example 2: This application discloses another method for charging a robot; please refer to [link / reference]. Figure 2This embodiment describes the entire process of charging multiple robots.

[0063] Step 201: All robots in area A start up simultaneously, acquire the current light intensity, and perform independent MPPT scans.

[0064] Step 202: The robot compares the light intensity with the pre-stored preset intensity to determine whether the light intensity is greater than the preset intensity. If yes, proceed to step 203. If no, proceed to step 216.

[0065] Step 203: The robot determines whether it received campaign request information during the MPPT scan. If yes, proceed to step 204. If no, proceed to step 205.

[0066] Step 204: As a responding robot, calculate its own power based on its own MPP parameters, and calculate the election power based on the MPP parameters in the election request information. Proceed to step 206.

[0067] Step 205: As a requesting bot, broadcast the campaign request information containing its own MPP parameters in area A, and upload its own MPP parameters to the platform. Proceed to step 209.

[0068] Step 206: Determine if your own power is less than or equal to the campaign power. If yes, proceed to step 207. If no, proceed to step 208.

[0069] Step 207: Act as a slave node. Proceed to step 212.

[0070] Step 208: Upload your MPP parameters to the platform.

[0071] Step 209: The platform calculates the power of each MPP parameter and selects the robot with the highest power as the master node.

[0072] Step 210: The platform sends the election completion information to the master node.

[0073] Step 211: The master node broadcasts its own master MPP parameters in area A every 10 seconds.

[0074] Step 212: Each slave node calculates the deviation rate based on the master MPP parameters and its own slave MPP parameters.

[0075] Step 213: Determine whether the deviation rate is less than or equal to 3% at the node. If yes, proceed to step 214. If no, proceed to step 215.

[0076] Step 214: The slave node charges using the master MPP parameters.

[0077] Step 215: The slave node is marked as an abnormal node and charged using the MPP parameters. Return to step 212.

[0078] Step 216: The robot charges according to its obtained MPP parameters.

[0079] The method described in this embodiment significantly improves charging efficiency through MPP parameter sharing, eliminating the need for slave nodes to perform complete independent scans. This reduces the time required for robots within the area to reach a stable charging state by 30%-50% (in actual testing with 100 robots in a sunny environment, the traditional method requires 200 seconds to reach stable charging, while this embodiment only requires 80-120 seconds). Furthermore, by using light intensity-assisted verification and abnormal slave node marking, the method enhances the anti-interference capability of charging operations within the area. Even in partially shaded scenarios, the charging efficiency of robots within the area can still be maintained above 85% (compared to only 60%-70% for traditional methods).

[0080] Based on the robot charging method disclosed in the above embodiments, this embodiment discloses a robot charging device. Please refer to... Figure 3 The robot charging device includes: a determining unit 301, a candidate unit 302, and a transmission unit 303; The determining unit 301 is used to determine the requesting robot and the election request information among the target robots; the target robot is the robot in the target area where the light intensity is greater than a preset intensity; the requesting robot is the robot among the target robots that first completes the maximum power point tracking scan and obtains the maximum power point (MPP) parameters; the election request information includes the MPP parameters of the requesting robot; The election unit 302 is used to elect a master node based on the election request information and the MPP parameters of the responding robot; the responding robot is a robot among the target robots other than the requesting robot; the master node is one of the target robots. The transmission unit 303 is used to transmit the master MPP parameters to the slave node at a preset frequency, so that the slave node can charge based on the master MPP parameters; the master MPP parameters are the MPP parameters of the master node; the slave node is a robot other than the master node in the target robot.

[0081] Optionally, the election unit 302 includes: The campaign transmission subunit is used by the requesting robot to transmit the campaign request information to each of the responding robots; The election response subunit is used for the requesting robot and the responding robot to compete for the master node in the target robot according to their respective MPP parameters.

[0082] Optionally, the campaign response subunit includes: Add a sub-unit to the set, used to add the requesting robot to the election set; The power calculation subunit is used by the response robot to calculate its own power based on its own MPP parameters and to calculate the campaign power based on the campaign request information. The non-participation in the election subunit is used so that the response robot does not participate in the election when its own power is less than or equal to the election power; The participating election subunit is used so that, when its own power is greater than the election power, the responding robot enters the election set; The master node election subunit is used to obtain the master node from the election set.

[0083] Optionally, the master node election subunit includes: The platform receiving subunit is used for robots in the election set to send their own MPP parameters to the platform. The platform election subunit is used to select the robot corresponding to the MPP parameter with the highest power among the received MPP parameters as the master node.

[0084] Optionally, the master node election subunit includes: The robot receiving subunit is used for the first robot, which is the first in the candidate set, to transmit its first MPP parameters to the second robot; the second robot is a robot in the candidate set other than the first robot. The robot removal subunit is used to remove the second robot from the campaign set when the second power is less than or equal to the first power; the second power is calculated from the second robot's own second MPP parameter; the first power is calculated from the first MPP parameter; A robot holding subunit is configured to keep the second robot in the campaign set when the second power is greater than the first power; The robot election subunit is used for repeated MPP parameter transmission and power comparison among the robots in the election set until the number of robots in the election set is one.

[0085] Optionally, the transmission unit 303 includes: The master node notification subunit is used by the platform to send election completion information to the master node. The master node transmission subunit is used by the master node in response to the election completion information to transmit the master MPP parameters to the slave node at the preset frequency.

[0086] Optionally, the device further includes: A deviation control unit is used to control the slave node corresponding to the slave power to charge based on the slave MPP parameters when the deviation between the slave power and the master power is greater than a preset value; the slave power is calculated from the slave MPP parameters; the master power is calculated from the master MPP parameters; and the slave MPP parameters are the MPP parameters of the slave node.

[0087] Optionally, the device further includes: A global parameter comparison unit is used to compare first information of the target area with second information of adjacent target areas at a global preset frequency; the first information includes the main MPP parameter or average light intensity of the target area, and the second information includes the main MPP parameter or average light intensity of the adjacent target areas. A synchronization unit is used to synchronize the first information and the second information into synchronization information when the first information and the second information are of the same type and the difference between them is less than a preset global difference; the synchronization information is the information with the larger value between the first information and the second information.

[0088] Optionally, the device further includes: The status monitoring unit is used to acquire the status of the master node in the target area at a preset monitoring frequency; The re-election unit is used to elect a new master node in the target area or call the master MPP parameters of an adjacent target area if the state is not obtained for a preset number of consecutive times.

[0089] Optionally, the device further includes: The raw parameter acquisition unit is used to acquire the raw master MPP parameters; the raw master MPP parameters are obtained by the master node performing an MPPT scan. The parameter calculation unit is used to calculate the processing parameters based on the original master MPP parameters and the recommended values ​​when the recommended values ​​are obtained; the recommended values ​​are obtained at a preset frequency and are related to the light intensity and temperature. The parameter determination unit is used to determine the parameter with the larger value among the processing parameters and the original master MPP parameters as the master MPP parameter.

[0090] Optionally, the transmission unit 303 includes: The broadcast subunit is used to broadcast the main MPP parameters via LoRa communication; The receiving subunit is used to control the slave nodes within a preset distance from the master node to simultaneously receive the master MPP parameters via LoRa communication and Bluetooth communication.

[0091] Based on the above-described method for charging a robot, this application also discloses a robot system, including a processor and a memory, wherein the memory is used to store a computer program, the computer program including instructions, and the instructions are executed by the processor to implement the above-described method.

[0092] The embodiments in this specification are described in a progressive manner. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant details can be found in the method section.

[0093] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0094] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0095] The features described in the embodiments of this specification can be substituted for or combined with each other, so that those skilled in the art can implement or use this application.

[0096] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for charging a robot, characterized in that, include: Identify the requesting robot and campaign request information within the target robot; The target robot is a robot in the target area where the light intensity is greater than a preset intensity; The requesting robot is the target robot that completes the maximum power point tracking scan first and obtains the maximum power point (MPP) parameters; the election request information includes the MPP parameters of the requesting robot; Based on the election request information and the MPP parameters of the responding robot, a master node is elected; the responding robot is the target robot other than the requesting robot. The master node is one of the target robots; The master MPP parameters are transmitted to the slave node at a preset frequency, enabling the slave node to charge based on the master MPP parameters; the master MPP parameters are the MPP parameters of the master node. The slave node is any robot in the target robot group other than the master node.

2. The method according to claim 1, characterized in that, The process of electing a master node based on the election request information and the MPP parameters of the response robot includes: The requesting robot transmits the campaign request information to each of the responding robots; The requesting robot and the responding robot compete for the master node among the target robots based on their respective MPP parameters.

3. The method according to claim 2, characterized in that, The requesting robot and the responding robot compete for the master node among the target robots based on their respective MPP parameters, including: Add the requesting robot to the election set; The response robot calculates its own power based on its own MPP parameters and calculates its campaign power based on the campaign request information. If its own power is less than or equal to the election power, the responding robot will not participate in the election; If its own power is greater than the election power, the responding robot enters the election set; Obtain the master node from the election set.

4. The method according to claim 3, characterized in that, The step of obtaining the master node from the election set includes: The robots in the campaign set send their own MPP parameters to the platform; The robot corresponding to the MPP parameter with the highest power among the received MPP parameters obtained by the platform is the master node.

5. The method according to claim 3, characterized in that, The step of obtaining the master node from the election set includes: The first robot, which is the first in the election set, transmits its first MPP parameters to the second robot; the second robot is any robot in the election set other than the first robot. If the second power is less than or equal to the first power, the second robot is removed from the election set; the second power is calculated from the second robot's own second MPP parameter; the first power is calculated from the first MPP parameter; When the second power is greater than the first power, the second robot remains in the election set; The robots in the election set repeatedly transmit MPP parameters and compare power until the number of robots in the election set is one.

6. The method according to claim 4, characterized in that, The transmission of master MPP parameters to slave nodes at a preset frequency includes: The platform sends election completion information to the master node; In response to the election completion information, the master node transmits the master MPP parameters to the slave node at the preset frequency.

7. The method according to any one of claims 1-6, characterized in that, After transmitting the master MPP parameters to the slave node at a preset frequency, the method further includes: If the deviation between the slave power and the master power is greater than a preset value, the slave node corresponding to the slave power is controlled to charge based on the slave MPP parameters; the slave power is calculated from the slave MPP parameters; the master power is calculated from the master MPP parameters; the slave MPP parameters are the MPP parameters of the slave node.

8. The method according to any one of claims 1-6, characterized in that, After the slave node is charged based on the master MPP parameters, the method further includes: The first information of the target area and the second information of the adjacent target areas are compared at a globally preset frequency; the first information includes the main MPP parameter or average light intensity of the target area, and the second information includes the main MPP parameter or average light intensity of the adjacent target areas. If the first information and the second information are of the same type and their difference is less than a preset global difference, the first information and the second information are synchronized into synchronization information; the synchronization information is the information with the larger value between the first information and the second information.

9. The method according to any one of claims 1-6, characterized in that, After the slave node is charged based on the master MPP parameters, the method further includes: The status of the master node in the target area is acquired at a preset monitoring frequency; If the state is not obtained for a preset number of consecutive times, a new master node will be elected within the target area, or the master MPP parameters of the adjacent target area will be called.

10. The method according to any one of claims 1-6, characterized in that, Before transmitting the master MPP parameters to the slave node at a preset frequency, the method further includes: Obtain the original master MPP parameters; the original master MPP parameters are obtained by the master node performing an MPPT scan. Once the recommended value is obtained, the processing parameters are calculated based on the original master MPP parameters and the recommended value; the recommended value is obtained at a preset frequency and is related to the light intensity and temperature. The parameter with the larger value among the processing parameters and the original master MPP parameters is determined as the master MPP parameter.

11. The method according to any one of claims 1-6, characterized in that, The transmission of master MPP parameters to slave nodes at a preset frequency includes: The master MPP parameters are broadcast via LoRa communication; The slave nodes within a preset distance from the master node simultaneously receive the master MPP parameters via LoRa and Bluetooth communication.

12. A device for charging a robot, characterized in that, include: The unit is defined as the selection unit, the election unit, and the transmission unit. The determining unit is used to determine the requesting robot and the campaign request information in the target robot; The target robot is a robot in the target area where the light intensity is greater than a preset intensity; The requesting robot is the target robot that completes the maximum power point tracking scan first and obtains the maximum power point (MPP) parameters; the election request information includes the MPP parameters of the requesting robot; The election unit is used to elect a master node based on the election request information and the MPP parameters of the responding robot; the responding robot is the target robot other than the requesting robot. The master node is one of the target robots; The transmission unit is used to transmit the master MPP parameters to the slave node at a preset frequency, so that the slave node can charge based on the master MPP parameters; the master MPP parameters are the MPP parameters of the master node. The slave node is any robot in the target robot group other than the master node.

13. A robot system, characterized in that, The device includes a processor and a memory, the memory being used to store a computer program, the computer program including instructions that, when executed by the processor, are used to implement the method according to any one of claims 1-11.

Images