CN116931599A - Route control method of photovoltaic power generation field dispatching robot - Google Patents

Abstract

The disclosure provides a route control method of a photovoltaic power generation field dispatching robot, which comprises the following steps: searching a feasible route of the photovoltaic power generation field under a first condition by a first autonomous mobile entity, and simultaneously collecting first sensor data of a plurality of objects contained in the feasible route by using a plurality of first sensors to create a storage route of the feasible route; searching the exercisable route under a second condition by a second autonomous mobile entity; determining a deviation between the second sensor data and the first sensor data; and creating an operation threshold of a dispatch robot using the deviation, the operation threshold of the dispatch robot to be included in the stored route and used by the dispatch robot as a threshold of a normal working condition when the dispatch robot is traveling; and controlling the dispatching robot to start and run from the position to the position of the cleaning robot to be processed at least based on the operation threshold value.

Description

Route control method of photovoltaic power generation field dispatching robot

Technical Field

The disclosure relates to a route control method of a photovoltaic power generation farm dispatching robot.

Background

Cleaning of photovoltaic panels is critical to the performance and efficiency of solar energy systems. Over time, the solar panel surface can accumulate dust, dirt, and other contaminants that can reduce the absorptive capacity and conversion efficiency of the photovoltaic cells. Therefore, periodic cleaning is critical to maintaining efficient operation of the solar energy system.

However, conventional cleaning methods tend to be time consuming, laborious and inefficient. To solve this problem, photovoltaic robotic systems have been developed. A photovoltaic robotic system is an autonomous mobile robotic system specifically designed for wet cleaning on a photovoltaic panel. The system combines advanced robotics, sensor technology and communication technology to be able to intelligently sense environmental conditions and perform cleaning tasks. However, to achieve the scale effect, it is a problem to be solved how to arrange to implement at least one photovoltaic robot, how to coordinate the problems of handling, transporting, and maintenance in the photovoltaic power generation field between multiple photovoltaic robots, so as to implement the scale and intelligent operation. At present, most dispatching robots are controlled by a main controller, the flexibility of processing burst time is poor, and the control method has become one main factor affecting the operation efficiency and large-scale application of the photovoltaic robots.

Disclosure of Invention

In order to solve one of the above technical problems, the present disclosure provides a route control method of a photovoltaic farm dispatch robot.

According to one aspect of the present disclosure, there is provided a route control method of a photovoltaic farm dispatch robot, including:

searching, by the first autonomous mobile entity, for a traversable route of the photovoltaic power plant under a first condition while collecting first sensor data of a plurality of objects contained within the traversable route using a plurality of first sensors included in the first autonomous mobile entity, and wherein the first condition includes at least one of weather conditions and time in the photovoltaic power plant;

creating a routable stored route using the first sensor data for use by the dispatch robot when traversing the photovoltaic power generation field;

searching for the drivable path under a second condition by a second autonomous mobile entity while collecting second sensor data of a plurality of objects contained within the drivable path using a plurality of second sensors included in the second autonomous mobile entity, wherein the plurality of second sensors includes at least one sensor of the same type as the plurality of first sensors, and wherein the second condition includes that the photovoltaic cleaning robot is to be processed, the second sensor data including at least an image/video of an environment of a location of the photovoltaic cleaning robot to be processed;

Determining a deviation between second sensor data representative of the plurality of objects detected under the second condition and first sensor data representative of the plurality of objects detected under the first condition; and

creating an operation threshold of a dispatch robot to be included in the storage route using the deviation, and to be used by the dispatch robot as a threshold of a normal operation condition when the dispatch robot is traveling;

and controlling the dispatching robot to start and run from the position to the position of the cleaning robot to be processed at least based on the operation threshold value.

According to at least one embodiment of the present disclosure, the first sensor and the second sensor each comprise at least a GPS sensor, an image/video sensor, a lidar sensor.

According to at least one embodiment of the present disclosure, the dispatch robot is configured to travel on multiple ones of the available routes of the photovoltaic power generation field for the carrying and maintenance of at least one photovoltaic cleaning robot within the photovoltaic power generation field.

According to at least one embodiment of the present disclosure, the dispatch robot includes a plurality of third sensors, wherein the third sensors include at least one sensor of the same type of the first sensor and/or second sensor.

In accordance with at least one embodiment of the present disclosure, wherein the dispatch robot is configured to detect an abnormal operating condition exceeding the operational threshold using the third sensor when traversing a runnable route.

According to at least one embodiment of the present disclosure, the abnormal operating condition includes at least one newly-emerging entity not represented in the first sensor data and the second sensor data, and wherein the at least one newly-emerging entity includes a vehicle, an operator, a photovoltaic cleaning robot, and other dispatch robots that block a dispatch robot from currently traveling a route.

According to at least one embodiment of the present disclosure, the abnormal operating condition includes at least one new occurrence not represented in the first sensor data and the second sensor data, the at least one new occurrence including an abrupt weather condition affecting a current travel route of the dispatch robot.

According to at least one embodiment of the present disclosure, further comprising notifying, by the dispatch robot, a photovoltaic power farm main server of a control center when the dispatch robot detects an abnormal operating condition; and receiving a command from the photovoltaic power generation field main server through the dispatching robot until the operation threshold of the dispatching robot is not exceeded or the abnormal working condition is relieved.

According to at least one embodiment of the present disclosure, the first autonomous mobile entity and the second autonomous mobile entity are one of an autonomous mobile vehicle and an autonomous mobile vehicle.

According to at least one embodiment of the present disclosure, the first autonomous mobile entity and the second autonomous mobile entity are both autonomous mobile aircraft. In at least one embodiment, the loading and unloading position comprises a base station position in the photovoltaic power generation field and/or a photovoltaic panel position in the photovoltaic power generation field.

Drawings

The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the disclosure and together with the description serve to explain the principles of the disclosure.

Fig. 1 is a schematic diagram of a dispatch robot according to one embodiment of the present disclosure.

FIG. 2 is a block diagram schematic of a sensor array for generating routable routes according to one embodiment of the present disclosure.

Fig. 3 is a schematic view of a photovoltaic farm portion generating a dispatch robot routable route in accordance with one embodiment of the present disclosure.

Fig. 4 is a schematic block diagram of computer logic of a photovoltaic farm main server according to one embodiment of the present disclosure.

Fig. 5 is a logic flow diagram of generating a dispatch robot routable route in accordance with one embodiment of the present disclosure.

Detailed Description

The present disclosure is described in further detail below with reference to the drawings and the embodiments. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant content and not limiting of the present disclosure. It should be further noted that, for convenience of description, only a portion relevant to the present disclosure is shown in the drawings.

In addition, embodiments of the present disclosure and features of the embodiments may be combined with each other without conflict. The technical aspects of the present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Unless otherwise indicated, the exemplary implementations/embodiments shown are to be understood as providing exemplary features of various details of some ways in which the technical concepts of the present disclosure may be practiced. Thus, unless otherwise indicated, features of the various implementations/embodiments may be additionally combined, separated, interchanged, and/or rearranged without departing from the technical concepts of the present disclosure.

The use of cross-hatching and/or shading in the drawings is typically used to clarify the boundaries between adjacent components. As such, the presence or absence of cross-hatching or shading does not convey or represent any preference or requirement for a particular material, material property, dimension, proportion, commonality between illustrated components, and/or any other characteristic, attribute, property, etc. of a component, unless indicated. In addition, in the drawings, the size and relative sizes of elements may be exaggerated for clarity and/or descriptive purposes. While the exemplary embodiments may be variously implemented, the specific process sequences may be performed in a different order than that described. For example, two consecutively described processes may be performed substantially simultaneously or in reverse order from that described. Moreover, like reference numerals designate like parts.

When an element is referred to as being "on" or "over", "connected to" or "coupled to" another element, it can be directly on, connected or coupled to the other element or intervening elements may be present. However, when an element is referred to as being "directly on," "directly connected to," or "directly coupled to" another element, there are no intervening elements present. For this reason, the term "connected" may refer to physical connections, electrical connections, and the like, with or without intermediate components.

For descriptive purposes, the present disclosure may use spatially relative terms such as "under … …," under … …, "" under … …, "" lower, "" above … …, "" upper, "" above … …, "" higher "and" side (e.g., as in "sidewall"), etc., to describe one component's relationship to another (other) component as illustrated in the figures. In addition to the orientations depicted in the drawings, the spatially relative terms are intended to encompass different orientations of the device in use, operation, and/or manufacture. For example, if the device in the figures is turned over, elements described as "under" or "beneath" other elements or features would then be oriented "over" the other elements or features. Thus, the exemplary term "below" … … can encompass both an orientation of "above" and "below". Furthermore, the device may be otherwise positioned (e.g., rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, when the terms "comprises" and/or "comprising," and variations thereof, are used in the present specification, the presence of stated features, integers, steps, operations, elements, components, and/or groups thereof is described, but the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof is not precluded. It is also noted that, as used herein, the terms "substantially," "about," and other similar terms are used as approximation terms and not as degree terms, and as such, are used to explain the inherent deviations of measured, calculated, and/or provided values that would be recognized by one of ordinary skill in the art.

A photovoltaic farm typically comprises more than one dispatch robot 10 and at least one main server, which may communicate with each other via, for example, a communication network. The dispatch robot 10 is used to dispatch and load and unload a photovoltaic cleaning robot in a photovoltaic power generation field. One embodiment of a dispatch robot 10 is shown in fig. 1. As shown in fig. 1, dispatch robot 10 includes a controller 101, a communication device 102, a navigation device 103, a GPS device 104, a data storage device 105, a display 106, a user input interface (not shown), a sensor array (not shown), and any other type of device commonly found in dispatch robots 10 as understood in the art, such as a handling device, a lifting device, and a drive device.

The controller 101 includes a processor, such as a microcomputer, with a control program that controls the dispatch robot 10 as discussed herein. The processor may be part of a microcomputer. The controller 101 may also include other conventional components such as input interface circuitry, output interface circuitry, and storage devices such as ROM (read only memory) devices and RAM (random access memory) devices. The internal RAM of the controller 101 may store the state of the operation flag, various control data, etc., and the internal ROM of the controller 101 may store a control program and any of various operations understood in the art. The controller 101 is operatively coupled with and programmed to monitor and control the communication device 102, the navigation device 103, the GPS device 104, the data storage device 105, the display 106, the user input interface, the sensor array, and other types of devices on the dispatch robot 10 in any suitable manner as understood in the art, as discussed herein. The storage device 105 may also store information received from another dispatch robot, a host server, and/or a photovoltaic robot and any other entity discussed herein.

The communication device 102 includes, for example, a receiver and a transmitter configured as separate components or as a transceiver, as well as any other type of device for wireless communication. For example, the communication device 102 is configured to communicate wirelessly via one or more communication routes. Examples of communication routes include cellular telephone networks, wireless networks, dedicated short-range communication networks, power line communication networks, and the like. The communication device 102 is configured to receive information from an external source and transmit such information to the controller 101. For example, the communication device 102 may communicate with the primary server via, for example, a communication network, direct communication, or in any suitable manner as understood in the art. The communication device 102 may also communicate with another dispatch robot 10, one or more photovoltaic cleaning robots, or any other suitable entity (e.g., a transmitter disposed on a photovoltaic panel) through, for example, a communication network, direct communication, or in any suitable manner as understood in the art.

The navigation device 103 is configured to receive information about the recommended travel route of the dispatch robot 10, for example, from the controller 101. The suggested travel route may be determined based on information received by the controller 101 from, for example, a mobile application connected to the dispatch robot 10, based on a travel pattern of the dispatch robot 10 determined using the methods, devices, and systems described herein below. The navigation device 103 may also communicate with the GPS device 104 to determine the suggested travel route. The controller 101 may use information received from the navigation device 103 and the GPS device 104 to control the scheduling of the exercise of the robot 10, as is understood in the art. The navigation device 103 may also communicate with, for example, a main server and the photovoltaic cleaning robot using the communication device 102, directly or in any other suitable way.

The data storage device 105 may be any suitable type of memory or storage in which data may be stored or from which data may be retrieved. The display 106 may be any suitable type of display screen, such as a liquid crystal screen, a touch pad, a flat panel display, or the like. The user input interface may be, for example, a touch pad on a display, a gesture sensing device, mechanical or virtual buttons on a steering wheel, or any other suitable location within or external to dispatch robot 10 discussed herein, and so forth. In one embodiment, the user input interface may also be a separate device, such as a smart phone, tablet, notebook, or any other suitable device type, that may communicate with the controller 101, such as through the communication device 102 or in any other suitable manner.

As understood in the art, the dispatch robot 10 should also be configured with multiple types of sensors configured to monitor and sense the environment surrounding the dispatch robot 10 and detect objects in the vicinity of the dispatch robot 10. The sensors are installed to be external on the front of the dispatch robot 10, and on the rear. However, the sensors may be mounted on any suitable external portion of the dispatch robot 10, including front and rear bumpers or any suitable combination of areas. The sensors communicate with the controller 101, which can then use the information provided by the sensors to control the dispatch robot 10 and perform the operations discussed herein, as will be described in greater detail below.

In embodiments of the present disclosure, the first step in constructing a safe, traversable route algorithm is to determine the work area. This step mainly involves the determination and definition of the range of motion of the scheduling robot 10. Specifically, the working area may be a broad photovoltaic power generation field, or may be limited to a specific photovoltaic panel area within the power generation field.

When the working area is set, the working area is defined according to the actual application requirements. For example, the primary task of dispatch robot 10 is to transport and rescue the photovoltaic cleaning robot, and then the work area may need to contain all of the photovoltaic panel area that needs to be cleaned. If the task of the robot is to monitor or maintain the equipment of the photovoltaic power plant, the work area may need to include an area where all the equipment is distributed.

After determining the working area, the dispatch robot 10 will navigate autonomously within this area. To accomplish this, dispatch robot 10 needs to rely on Geographic Information System (GIS) and Global Positioning System (GPS) technologies to obtain environmental information, including terrain, obstructions, device locations, etc. The dispatch robot 10 may then plan its own course of action based on this information to avoid collisions and other possible hazards while completing the task.

Environmental changes also need to be taken into account when defining the working area. For example, due to sudden extreme weather (storms, storm winds, snow storms, heavy fog) and the like, real-time adjustments may be required in the work area. Therefore, the dispatch robot 10 needs to have a fast response capability to environmental changes so that its own action strategy and route planning can be adjusted in time when the environment changes.

The starting address, which is the location from which the dispatch robot 10 starts, may be a storage warehouse of the dispatch robot 10 or the photovoltaic cleaning robot, or a charging base station. Further, it may be a position where the dispatch robot 10 is in an idle state in the photovoltaic power generation field. It should be noted that the starting address must be a safe place to ensure that the dispatch robot 10 is able to avoid any possible danger during the course of action. The precise identification and location of the start address is critical to safe and efficient route planning. For example, if the starting address is located on rough or unstable ground, additional stabilization devices or countermeasures may be required to ensure proper operation of the robot.

Then the determination of the destination. In a photovoltaic farm, the possible destination addresses need to be listed and assigned well-defined coordinates. These destinations may include areas of the photovoltaic panels where the photovoltaic cleaning robots need to be handled, areas of the roads where the photovoltaic robots need to be rescued from falling, equipment that needs to be serviced, or specific locations that need to be monitored. In this step, GIS (geographic information system) or GPS (global positioning system) and picture and video recognition techniques may be applied to achieve accurate location and description of the destination.

Note that the process of determining the starting address and destination may involve multiple interaction steps. For example, if the destination is a photovoltaic panel location where it is desired to load and unload the photovoltaic cleaning robot, it may be necessary to first monitor using a sensor or camera and adjust the location of the destination based on this information. Meanwhile, the dispatch robot 10 may need to be able to cope with various uncertainties from the environment, such as weather changes, equipment failures, etc., and to update its own route planning in real time.

In one embodiment of the present disclosure, safe and feasible routes are pre-determined by autonomous mobile entities to improve the reliability of scheduling robots to travel to destinations at safe universities. Autonomous mobile entities may be vehicles and aircraft equipped with autonomous mobile devices. In one embodiment of the present disclosure, an autonomous mobile vehicle is employed to act as the autonomous mobile entity. The autonomous mobile vehicle performs a pre-flight survey of the selected work area before the dispatch robot 10 initiates its operational mission, collecting the necessary data. This process is a key step for forming a safe and traversable route that can provide important information support for robot travel. Particularly, when the photovoltaic cleaning robot fails or falls, the process can effectively assign the most preferable route to the dispatching robot 10, and avoid that the dispatching robot 10 can detour for a long time and cannot reach the assigned place.

In the aspect of terrain feature analysis, autonomous mobile aircraft are equipped with high-precision cameras and other related sensors for acquiring detailed terrain information of the ground. Such information includes differences in topography, slope changes, flatness of the ground, etc., which are important factors for evaluating the influence of ground conditions on the running of the robot. For example, an excessively steep grade or an excessively uneven ground may increase the risk of the dispatch robot rolling over or getting caught in which places need to be avoided in route planning.

Obstacle recognition is another important link. Autonomous mobile aircraft recognize various obstacles on the ground through vision systems or radar systems, including static obstacles such as rocks, equipment, buildings, etc., as well as dynamic obstacles such as moving vehicles, operators, etc. These obstacle information will be recorded and transmitted to a data analysis module, which is used to evaluate and plan the travel route of the robot.

In addition, autonomous mobile aircraft also require precise positioning of the device location within the farm. Through GPS or other geographic information systems, the autonomous mobile aircraft can acquire the accurate positions of all devices in the power generation field, including photovoltaic panels, power transformation devices, energy storage devices and the like. The location information of these devices is essential for scheduling the robot 10 to perform maintenance or inspection tasks.

Autonomous mobile aircraft also require evaluation of road hardness, wet skid, degree of breakage, etc. These road surface conditions have a direct influence on the traveling performance of the dispatch robot 10. For example, a road surface that is too slippery may increase the risk of the dispatch robot 10 sliding, while a road surface that is too damaged may prevent the dispatch robot 10 from traveling properly.

After the above environmental data is collected, the data is sent to a data analysis module for processing and analysis. The data analysis module processes and analyzes the collected data according to preset algorithms and criteria to determine which routes are safe and feasible. The data analysis module may also evaluate and rank multiple possible routes, if any, to select an optimal route for use by the dispatch robot 10.

In one embodiment of the present disclosure, the autonomous mobile vehicle may also receive some or all of the control of a person. Such autonomous mobile vehicles may be fixed-wing autonomous mobile vehicles or rotary-wing autonomous mobile vehicles, depending on the actual application requirements and environmental conditions. Both the selection and the manner of use of the autonomous mobile vehicle will directly affect the effectiveness and efficiency of the collection of environmental data.

Under the working condition that certain gradients are relatively flat, the ground robot can be used for completing the task of autonomously moving the aircraft. Such a floor robot may be equipped with various sensors including, but not limited to, lidar, infrared cameras, ultrasonic sensors, etc., for collecting detailed information of the floor. This information can also be used to evaluate and plan the travel route of the robot.

According to the method, the autonomous mobile aircraft or the ground robot is utilized to conduct the environmental investigation and data collection in advance, then the data analysis module is utilized to conduct information processing and analysis, the environmental investigation and the data collection are conducted again under the condition that the scheduling robot needs to be called, the obstacle and the danger in the current environment are effectively identified through the differential comparison of the two information, the safety guarantee is provided for the running of the robot, and the automation degree and the working efficiency of the photovoltaic power generation field are improved.

After the data analysis module completes processing and analysis of the environmental data, if a route is confirmed as safe and traversable, the route will be marked as a confirmed route. This validation process involves a comprehensive assessment of all relevant factors in the route, including the terrain conditions on the route, obstructions, device locations, road conditions, climatic conditions, etc.

Once the route is confirmed, it will be entered into the database and stored as a new safe route. This database is an important component of the system that provides real-time and reliable route information for scheduling the travel of the robot 10. Each route in the database is subject to strict security validation and is considered secure and traversable. When the dispatch robot 10 needs to travel from a starting point to a destination, it can query the database and select a most appropriate route for traveling. The routing of the robot may be based on various factors such as the length of the route, the terrain conditions on the route, the current environmental conditions, etc. By the mode, the robot can effectively complete tasks on the premise of ensuring safety.

In one embodiment of the present disclosure, it is important that for a validated route, its effectiveness and safety need to be continuously verified and updated during the actual operation of the dispatch robot 10. To achieve this, the present disclosure employs a dynamic data collection and route update mechanism that collects real-time environmental data by scheduling sensor arrays onboard the robot 10 to again verify and revise the validated route in real-time.

Referring now to fig. 2, there is shown a preferred embodiment of the present disclosure where the sensor array is configured on an autonomous mobile entity with wide applicability and significant utility value. Taking dispatch robot 10 as an example, the present sensor array may comprise a variety of sensors including, but not limited to, laser rangefinders, global Positioning Systems (GPS), video recorders, ultrasonic sensors, radar sensors, gyroscopes, and odometers. In another embodiment of the present disclosure, the sensor array may include more sensors, such as temperature sensors and humidity sensors, to meet the needs of a particular application scenario. The integration of these sensors provides the autonomous dispatch robot 10 with comprehensive environmental information that allows the dispatch robot 10 to more efficiently navigate in complex environments. For example, a laser rangefinder may accurately measure the distance of the dispatch robot 10 from surrounding objects in order to avoid collisions with obstacles; the global positioning system can provide the dispatching robot 10 with accurate position information in the power generation field so as to formulate an optimal driving route; the video recording device may capture real-time images of the environment, helping the dispatch robot 10 to identify the condition of the road surface and predict potential obstacles; the ultrasonic sensor can find obstacles in a low visual environment, so that additional safety guarantee is provided; the odometer can track the travel distance and speed of the dispatch robot 10, which facilitates accurate route planning and control of the dispatch robot 10.

It should be noted that the dispatch robot 10 equipped with such a sensor array can monitor environmental changes in real time and can timely detect and respond appropriately, such as halting travel or changing travel routes, when an abnormal situation is encountered, such as an obstacle or a sudden appearance of a worker. This has an extremely important role in ensuring the operational safety of the photovoltaic power generation field.

In addition, such sensor arrays also need to take into account various objects present in the photovoltaic power generation field, such as photovoltaic cleaning robots, photovoltaic panel sets, charging base stations, storage warehouses, operators, and the route itself, etc., when forming the environment. On this basis, different sensors can detect different types of objects, for example, a radar sensor can identify the position of the photovoltaic panel set, and a camera can identify a ramp or turn on the route. This identification capability facilitates more accurate positioning and navigation of the dispatch robot 10 in the photovoltaic power generation field.

Such sensor arrays need to take into account the characteristics of the photovoltaic power generation field adequately when mapping traversable routes. When a photovoltaic panel group is identified, the dispatch robot 10 may need to change course to avoid collisions; when a ramp or turn is identified, dispatch robot 10 may need to adjust the travel direction to accommodate the terrain variation; in addition, when a route is identified, the dispatch robot 10 may also activate additional sensors to scan other moving objects at the intersection, such as other dispatch robots 10 or operators.

The output data of these sensors is fed into the processor of the controller 101 in real time for processing and analysis. The processor may perform a comprehensive evaluation on the collected data to determine the safety and feasibility of the current travel route. If a potential hazard or obstacle is found, dispatch robot 10 may immediately respond, such as by suspending travel, alerting, or adjusting the travel route.

To more accurately assess the safety and feasibility of a route, the present disclosure employs empirical or bayesian methods to determine the maximum threshold for each sensor. This threshold is a sensitivity setting of the dispatch robot 10 to various environmental factors during travel beyond which the dispatch robot 10 may determine a potential risk or obstruction.

During actual operation, the validated route may need to be validated and revised multiple times under different conditions. These conditions include different weather conditions (e.g., sunny, rainy, foggy, windy, etc.), different times of the day (e.g., daytime, nighttime, dusk, dawn, etc.), and different device states (e.g., state of charge, state of load, state of failure, etc.). Such multi-condition route verification and correction can make the travel of the dispatch robot 10 safer and more reliable.

In one embodiment of the present disclosure, if an autonomous mobile vehicle finds a route potentially risky or obstructed during data collection and analysis, the route will be marked as an unacknowledged route and specifically identified in the route database. These unacknowledged routes are considered to be an uncertainty or risk for the travel of the dispatch robot 10 and are therefore temporarily excluded from the travel range of the dispatch robot 10.

These unacknowledged routes may not be traversed by the dispatch robot 10 for various reasons, e.g., there may be safety hazards such as steep slopes, unstable floors, etc.; there may be obstacles that are difficult to avoid, such as sites being constructed, blocked sites, etc.; or there may be unpredictable factors such as emergency events, severe weather conditions, etc.

When the autonomous mobile vehicle finds an unacknowledged route, it does not immediately stop data collection and analysis of the area. Instead, it will continue to look for the area, try to find other possible safe routes, or again observe and analyze the unacknowledged route from a different angle or altitude, to see if a new method or route can be found to traverse the obstacle.

After the autonomous mobile vehicle completes the lookup of the entire working area, if there are still unidentified routes, they will remain in their unidentified state in the route database until the next data collection and analysis process is confirmed as safe or determined as permanently unable to be traversed.

In some cases, if an unacknowledged route is critical to the completion of work, other resources or devices may need to be invoked to solve this problem. For example, obstacles on a route may be removed by manual intervention, or other types of dispatch robots 10 or devices may be invoked to accomplish the task of this route.

In all cases, the objective of the present disclosure is to ensure the safety and effectiveness of the dispatch robot 10, through dynamic data collection and analysis, real-time route updating and optimization, and aggressive handling of unacknowledged routes, enabling the dispatch robot 10 to efficiently complete tasks in a variety of complex environments.

In fig. 3, a partial map of a photovoltaic power generation field is depicted, including a plurality of photovoltaic power generation panel sets 40 drawn by autonomous mobile aircraft along a safe traversable route 30, in accordance with one embodiment of the present disclosure. These routes 30 form a network covering the user selected area and associated with various devices and structures within the area, such as photovoltaic panel assemblies 40, buildings 50, charging base stations 60, and the like.

Photovoltaic power generation fields are a complex environment that includes various terrains, facilities and equipment, such as hills, flat lands, photovoltaic panels, supporting structures, power equipment, energy storage devices, transmission devices, monitoring devices, and the like. The task of the autonomous mobile vehicle is to draw one or more safe traversable routes 30 from the start point to the end point based on the collected vision and sensor data in such an environment.

The start and end points of these routes 30 may be any location within a photovoltaic farm where it is desired to schedule the robot 10 for construction operations or for charging. For example, the starting point may be a storage location of the dispatch robot 10 and the ending point may be a photovoltaic panel location where the dispatch robot 10 needs to perform cleaning work. Or the starting point is the position of the photovoltaic panel where the dispatch robot 10 is operating, and the end point is the position of the base station where the dispatch robot 10 needs to be charged.

In embodiments of the present disclosure, an autonomous mobile vehicle may choose to find all or part of a user selected area, collecting environmental data for those areas. This process may include the observation of terrain, the identification of obstructions, the location of equipment, etc. During the search process, the autonomous mobile vehicle may employ different flight modes and strategies, for example, it may search according to a preset flight path 30, or may dynamically adjust the flight path 30 according to actual environmental conditions. Autonomous mobile aircraft may choose to traverse all devices within the photovoltaic power generation field to obtain more environmental data, and may choose to bypass some devices.

After the autonomous mobile vehicle has completed data collection, the data is sent to a data analysis module for processing and analysis. The data analysis module processes and analyzes the collected data according to preset algorithms and criteria to determine which routes 30 are safe to use. If there are multiple possible routes 30, the module may also evaluate and rank them, selecting the optimal route 30 for use by the dispatch robot 10.

In general, the present disclosure enables the drawing of a safe, feasible, optimized route 30 in a complex photovoltaic farm environment through the flight lookup of an autonomous mobile aircraft, and the advanced processing and analysis of the collected data, providing accurate, reliable navigation information for scheduling the travel of the robot 10.

In one embodiment of the present disclosure, the method is implemented by an automated system comprising a main server of a photovoltaic power generation field, at least one autonomous mobile vehicle and at least one dispatch robot 10. As shown in fig. 4, the main server includes a control device 201, a display device 202, a user interface 203, a communication device 204, and a storage device 205. The control device includes a processor, such as a microcomputer, whose control program controls the components of the main server, and controls the dispatch robot 10 when the remote operation control of the dispatch robot 10 is performed. The processor may be part of a microcomputer. The control device may also include other conventional components such as input interface circuitry, output interface circuitry, and storage devices such as read-only memory devices and random access memory devices. The internal random access memory of the control device may store the state of the operation flags, various control data, etc., while the internal read only memory device of the control device may store control programs and any of various operations as understood in the art.

The control device controls the display device 202 to display information related to the operation of the main server, information related to the dispatch robot 10, information received from the photovoltaic cleaning robot, and any other suitable information as understood in the art. The display device 202 may be, for example, an LCD display, a touch pad, a flat panel display, or any other suitable display type known in the art. The user interface 203 may be, for example, a touch pad on the display device 202, a gesture sensing device, mechanical or virtual buttons, and so forth, as is understood in the art. The user interface 203 may also be a separate device, such as a smart phone, tablet, notebook, or any other suitable device type, which may communicate with the control device via, for example, the communication device 204 or in any other suitable manner.

Communication device 204 includes, for example, a receiver and a transmitter configured as separate components or as a transceiver, as well as any other type of device for wireless communication. For example, the communication device 204 is configured to wirelessly communicate with the dispatch robot 10, other host servers, photovoltaic cleaning robots, other types of content or service providers, and any other type of suitable entity discussed herein, such as receiving climate forecast information, including text, sounds, images, and the like, via one or more communication routes. Examples of communication routes include cellular telephone networks, wireless networks, dedicated short-range communication networks, power line communication networks, and the like. The communication device 102 may communicate with the dispatch robot 10 through, for example, a communication network or in any suitable manner as understood in the art. The communication device 204 may also communicate with the photovoltaic cleaning robot, another host server, or any other suitable entity, for example, through a communication network or in any suitable manner as understood in the art.

The storage device 205 may be any suitable type of memory or storage into which data may be stored and from which data may be retrieved. The storage device 205 may store processing results and control programs executed by the control device, such as processing results and control programs for the display device 202, the user interface 203, and the communication device 204, as well as any other suitable information. The photovoltaic cleaning robot may be capable of communicating with a host server to provide the host server with information related to, for example, the dispatch robot 10, the environment or conditions surrounding the dispatch robot 10 or related to the dispatch robot 10, the status of the drive equipment of the dispatch robot 10, and the like.

Fig. 5 illustrates a logic flow diagram for generating a dispatch robot routable route in accordance with one embodiment of the present disclosure. The method begins when a photovoltaic farm worker is to begin identifying a route.

The first autonomous mobile entity searches the exercisable route of the photovoltaic power generation field under the first condition, and in the embodiment, the first autonomous mobile entity is an autonomous mobile aircraft, and the autonomous mobile aircraft is high in efficiency and is not influenced by the ground condition, so that the autonomous mobile aircraft is preferred to be used as a search implementer of the exercisable route. The autonomous mobile aircraft carries various sensors, such as radar, ultrasound, optical image sensors, and Global Positioning System (GPS), for collecting data of an operating environment. The dispatch robot 10 then moves on a designated route to perform its preset tasks, such as placing a photovoltaic cleaning robot onto a target photovoltaic panel, or recycling a photovoltaic robot, etc.

During operation of the system, the autonomous mobile vehicle may make multiple searches for a specified route. During the lookup process, the autonomous mobile aircraft will collect various data, such as terrain data, weather data, time data, etc., using its onboard sensors. These data may help the system determine the operating range of dispatch robot 10. This operating range is set based on sensor data at specific environmental factors, such as different time periods of the day, various weather conditions, and different terrains. The collected data is sent to a data analysis module. The module analyzes the data using preset algorithms and criteria and sets the operating range of the dispatch robot 10 accordingly. This operating range defines the normal operating range of the dispatch robot 10 in a variety of different environments, providing guidance for the operation of the dispatch robot 10.

During operation of the dispatch robot 10, if the readings of any of its sensors exceed a set operating range threshold, then it is indicated that the dispatch robot 10 may have deviated from a normal operating environment. For example, if a radar or ultrasonic sensor detects an obstacle on the route, an optical sensor detects the presence of other personnel or other dispatch robots 10 on the route of the dispatch robot 10, a loss of GPS signal, or a failure of either sensor, which may cause the sensor readings to exceed a set operating range threshold.

When this occurs, an alarm will be triggered and this alarm information will be sent to the controller of the dispatch robot 10. After the controller receives the alarm, it will evaluate the current environmental conditions and decide on the next operation. If the situation is severe, it may be necessary to notify the photovoltaic farm main server of the situation. After receiving the alarm information, the remote operator at the main server performs semi-automatic or manual remote operation according to the received alarm information and the data of the video, radar and other sensors in real time, and adjusts the route or operation of the dispatch robot 10 until the readings of the sensors return to the set operation range.

In the embodiment of the present disclosure, by collecting, analyzing and processing data in various operating environments and precisely setting an operating range, the scheduling robot 10 can be effectively managed and controlled in a complex environment, thereby improving the working efficiency and safety of the scheduling robot 10. In addition, the present disclosure also provides an effective method of handling abnormal situations, which can give an alarm in time when the dispatch robot 10 deviates from the normal operation environment and take necessary operations to correct such deviation to ensure safe and effective operation of the dispatch robot 10, which is driven to the place where the cleaning robot to be handled is located.

In the description of the present specification, reference to the terms "one embodiment/manner," "some embodiments/manner," "example," "a particular example," "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment/manner or example is included in at least one embodiment/manner or example of the application. In this specification, the schematic representations of the above terms are not necessarily for the same embodiment/manner or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments/modes or examples. Furthermore, the various embodiments/modes or examples described in this specification and the features of the various embodiments/modes or examples can be combined and combined by persons skilled in the art without contradiction.

Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.

It will be appreciated by those skilled in the art that the above-described embodiments are merely for clarity of illustration of the disclosure, and are not intended to limit the scope of the disclosure. Other variations or modifications will be apparent to persons skilled in the art from the foregoing disclosure, and such variations or modifications are intended to be within the scope of the present disclosure.

Claims (10)

1. The route control method of the photovoltaic power generation field dispatching robot is characterized by comprising the following steps of:

searching, by the first autonomous mobile entity, for a traversable route of the photovoltaic power plant under a first condition while collecting first sensor data of a plurality of objects contained within the traversable route using a plurality of first sensors included in the first autonomous mobile entity, and wherein the first condition includes at least one of weather conditions and time in the photovoltaic power plant;

creating a routable stored route using the first sensor data for use by the dispatch robot when traversing the photovoltaic power generation field;

searching for the drivable path under a second condition by a second autonomous mobile entity while collecting second sensor data of a plurality of objects contained within the drivable path using a plurality of second sensors included in the second autonomous mobile entity, wherein the plurality of second sensors include at least one sensor of the same type as the plurality of first sensors, and wherein the second condition includes the presence of a photovoltaic cleaning robot to be processed within a photovoltaic farm, the second sensor data including at least an image/video of an environment in which the photovoltaic cleaning robot to be processed is located;

Determining a deviation between second sensor data representative of the plurality of objects detected under the second condition and first sensor data representative of the plurality of objects detected under the first condition; and

creating an operation threshold of a dispatch robot to be included in the stored route using the deviation, and used by the dispatch robot as a threshold of a normal operation condition when the dispatch robot travels;

and controlling the dispatching robot to start and run from the position of the dispatching robot to the position of the cleaning robot to be processed at least based on the operation threshold.

2. The method of claim 1, wherein the first sensor and the second sensor each comprise at least a GPS sensor, an image/video sensor, a lidar sensor.

3. The method of claim 1, wherein the dispatch robot is configured to travel on a plurality of the traversable routes of the photovoltaic power generation field for the carrying and maintenance of at least one photovoltaic cleaning robot within the photovoltaic power generation field.

4. The method of claim 1, wherein the dispatch robot includes a plurality of third sensors, wherein the third sensors include sensors of the same type as at least one of the first and/or second sensors.

5. The method of claim 1, wherein the dispatch robot is configured to detect an abnormal operating condition exceeding the operational threshold using the third sensor when traversing a runable route.

6. The method of claim 5, wherein the abnormal operating condition comprises at least one newly-emerging entity not represented in the first sensor data and the second sensor data, the at least one newly-emerging entity comprising a vehicle, an operator, a photovoltaic cleaning robot, and other dispatch robots that block a dispatch robot from currently traveling a route.

7. The method of claim 5, wherein the abnormal operating condition comprises at least one new occurrence not represented in the first sensor data and the second sensor data, the at least one new occurrence comprising an abrupt weather condition affecting a current travel route of the dispatch robot.

8. The method of claim 5, further comprising notifying, by the dispatch robot, a photovoltaic power farm master server of a control center when an abnormal operating condition is detected by the dispatch robot; and receiving a command from the photovoltaic power generation field main server through the dispatching robot until the operation threshold of the dispatching robot is not exceeded or the abnormal working condition is relieved.

9. The method of claim 1, wherein the first autonomous mobile entity and the second autonomous mobile entity are one of an autonomous mobile vehicle and an autonomous mobile vehicle.

10. The method of claim 1, wherein the first autonomous mobile entity and the second autonomous mobile entity are both autonomous mobile aircraft.