A control method, apparatus, device, and storage medium

Abstract

The present disclosure provides a control method, device, equipment and storage medium, the method comprises: obtaining a target area, and dividing the target area to obtain a plurality of corresponding sub-regions; obtaining access intensity information of each unmanned vehicle for the plurality of sub-regions, and determining at least one sub-region corresponding to each unmanned vehicle based on the access intensity information; for each unmanned vehicle, determining a target driving path corresponding to the unmanned vehicle according to the specified position information of each sub-region corresponding to the unmanned vehicle. By using the method, the control of multiple unmanned vehicles working together in the same area is realized through the access intensity information of each unmanned vehicle for the plurality of sub-regions, and the working efficiency of the unmanned vehicle is ensured.

Description

Technical Field

[0001] This disclosure relates to the field of information processing technology, and in particular to a control method, apparatus, device and storage medium. Background Technology

[0002] Currently, with the development of autonomous vehicle technology, it has been widely used for community patrols and area cleaning. Typically, for large areas, the efficiency of a single autonomous vehicle patrolling or cleaning is very low; therefore, multiple autonomous vehicles are usually needed to work together to improve efficiency.

[0003] However, how to control multiple unmanned vehicles working together in the same area and ensure their operational efficiency has become a pressing technical problem that needs to be solved. Summary of the Invention

[0004] This disclosure provides a control method, apparatus, device, and storage medium to at least solve the above-mentioned technical problems existing in the prior art.

[0005] According to a first aspect of this disclosure, a control method is provided, the method comprising:

[0006] Obtain the target region and divide it into multiple corresponding sub-regions;

[0007] Obtain access intensity information for each unmanned vehicle for the multiple sub-regions, and determine at least one sub-region corresponding to each unmanned vehicle based on the access intensity information;

[0008] For each autonomous vehicle, the target driving path is determined based on the specified location information of each sub-region corresponding to that autonomous vehicle.

[0009] In one possible implementation, acquiring the target region includes:

[0010] Determine the obstacle area where the obstacle target is located within the specified area;

[0011] The area obtained after removing the obstacle area from the specified area is determined as the target area.

[0012] In one possible implementation, obtaining access intensity information for each unmanned vehicle regarding the plurality of sub-regions, and determining at least one sub-region corresponding to each unmanned vehicle based on the access intensity information, includes:

[0013] When entering the loop cycle, the region division information corresponding to each unmanned vehicle and the access intensity information of each unmanned vehicle for each sub-region are obtained. The region division information is used to characterize the area occupied by the unmanned vehicle in the target area. The area occupied by the unmanned vehicle in the target area is the area composed of the various sub-regions occupied by the unmanned vehicle in the target area.

[0014] Based on the area division information and the access intensity information, determine the occupation status information of each unmanned vehicle in the target area, as well as the first access intensity and the second access intensity corresponding to each unmanned vehicle. The first access intensity corresponding to the unmanned vehicle is the minimum access intensity of the unmanned vehicle in each sub-area it occupies, and the second access intensity is the maximum access intensity of other unmanned vehicles adjacent to the unmanned vehicle in each sub-area it occupies.

[0015] For each autonomous vehicle, if the occupation status information indicates that the area occupied by each autonomous vehicle is the result of uniformly dividing the target area, and the first access intensity corresponding to the autonomous vehicle is greater than the second access intensity, the autonomous vehicle is controlled to access the first target sub-region currently occupied by the autonomous vehicle. The first target sub-region is the sub-region with the lowest access intensity among the sub-regions currently occupied by the autonomous vehicle.

[0016] If the occupation status information indicates that the area occupied by each unmanned vehicle is not the result of uniformly dividing the target area, and the first access intensity corresponding to the unmanned vehicle is greater than the second access intensity, the unmanned vehicle is controlled to access the second target sub-region. The second target sub-region is the sub-region occupied by the unmanned vehicle with the largest occupied area among the unmanned vehicles adjacent to the unmanned vehicle.

[0017] If the first access intensity corresponding to the unmanned vehicle is not greater than the second access intensity, control the unmanned vehicle to access the third target sub-region, the third target sub-region being the sub-region occupied by the unmanned vehicle adjacent to the unmanned vehicle;

[0018] At the end of the cycle, it is determined whether the target region has been uniformly divided.

[0019] If so, determine the unmanned vehicle information to which each sub-region belongs and the access intensity information corresponding to each sub-region, and obtain at least one sub-region corresponding to each unmanned vehicle;

[0020] If not, when entering the next cycle, return to the steps of obtaining the area division information corresponding to each unmanned vehicle and the access intensity information of each unmanned vehicle for each sub-area.

[0021] In one possible implementation, the designated location information of the sub-region is the center location of the sub-region;

[0022] For each autonomous vehicle, determining the target driving path corresponding to that vehicle based on the specified location information of each sub-region includes:

[0023] For each autonomous vehicle, the sub-regions occupied by the autonomous vehicle are divided into at least two grids, and the center of each grid is determined as the first center position;

[0024] The main path is determined based on the first center location;

[0025] The center position of each sub-region occupied by the autonomous vehicle is determined by the path formed around the main path as the target driving path of the autonomous vehicle.

[0026] In one possible implementation, the method further includes:

[0027] Detect whether the area occupied by each unmanned vehicle within the target area has changed;

[0028] If so, redetermine at least one sub-region corresponding to each autonomous vehicle.

[0029] According to a second aspect of this disclosure, a control device is provided, the device comprising:

[0030] The region division module is used to obtain the target region and divide the target region into multiple corresponding sub-regions;

[0031] The sub-region determination module is used to obtain access intensity information of each unmanned vehicle for the multiple sub-regions, and determine at least one sub-region corresponding to each unmanned vehicle based on the access intensity information.

[0032] The path determination module is used to determine the target driving path for each autonomous vehicle based on the specified location information of each sub-region corresponding to that autonomous vehicle.

[0033] In one possible implementation, the region division module is specifically used to determine the obstacle region where the obstacle target is located in the specified region; and to determine the region obtained after removing the obstacle region from the specified region as the target region.

[0034] In one possible implementation, the sub-region determination module is specifically used to, upon entering a loop cycle, acquire region division information corresponding to each unmanned vehicle and access intensity information of each unmanned vehicle for each sub-region. The region division information is used to characterize the region occupied by the unmanned vehicle in the target region, and the region occupied by the unmanned vehicle in the target region is the region composed of the various sub-regions occupied by the unmanned vehicle in the target region. Based on the region division information and the access intensity information, the module determines the occupancy status information of each unmanned vehicle in the target region, as well as the first access intensity and the second access intensity corresponding to each unmanned vehicle. The first access intensity corresponding to the unmanned vehicle is the minimum access intensity of the unmanned vehicle for the various sub-regions it occupies, and the second access intensity is the maximum access intensity of other unmanned vehicles adjacent to the unmanned vehicle for the various sub-regions it occupies. For each unmanned vehicle, if the occupancy status information indicates that the region occupied by each unmanned vehicle is the result of uniformly dividing the target region, and the first access intensity corresponding to the unmanned vehicle is greater than the second access intensity, the module controls the unmanned vehicle to access the first target sub-region currently occupied by the unmanned vehicle. The first target sub-region is the sub-region with the lowest access intensity among the sub-regions currently occupied by the autonomous vehicle. If the occupancy status information indicates that the area occupied by each autonomous vehicle is not the result of uniform division of the target region, and the first access intensity corresponding to the autonomous vehicle is greater than the second access intensity, the autonomous vehicle is controlled to access the second target sub-region, which is the sub-region occupied by the autonomous vehicle with the largest corresponding area among the autonomous vehicles adjacent to the autonomous vehicle. If the first access intensity corresponding to the autonomous vehicle is not greater than the second access intensity, the autonomous vehicle is controlled to access the third target sub-region, which is the sub-region occupied by the autonomous vehicle adjacent to the autonomous vehicle. At the end of the cycle, it is determined whether the target region is uniformly divided. If yes, the autonomous vehicle information to which each sub-region belongs and the access intensity information corresponding to each sub-region are determined to obtain at least one sub-region corresponding to each autonomous vehicle. If no, when entering the next cycle, the step of obtaining the region division information corresponding to each autonomous vehicle and the access intensity information of each autonomous vehicle for each sub-region is returned.

[0035] According to a third aspect of this disclosure, an electronic device is provided, comprising:

[0036] At least one processor; and

[0037] A memory communicatively connected to the at least one processor; wherein,

[0038] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the methods described in this disclosure.

[0039] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions for causing the computer to perform the methods described in this disclosure.

[0040] The control method, apparatus, device, and storage medium disclosed herein acquire a target area and divide the target area into multiple corresponding sub-regions; acquire access intensity information of each unmanned vehicle (UAV) for the multiple sub-regions, and determine at least one sub-region corresponding to each UAV based on the access intensity information; for each UAV, determine the target driving path corresponding to the UAV based on the specified location information of each sub-region corresponding to the UAV. In other words, by using the access intensity information of each UAV for the multiple sub-regions, control of multiple UAVs operating in the same area is achieved, ensuring the operational efficiency of the UAVs.

[0041] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0042] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation, in which:

[0043] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

[0044] Figure 1 A schematic flowchart of a control method provided in an embodiment of this disclosure is shown;

[0045] Figure 2 This illustration shows a flowchart of a process for determining the area corresponding to an unmanned vehicle, provided by an embodiment of this disclosure.

[0046] Figure 3 A schematic diagram of a control method provided in an embodiment of this disclosure is shown;

[0047] Figure 4 A schematic diagram of the composition structure of an electronic device provided in an embodiment of this disclosure is shown. Detailed Implementation

[0048] To make the objectives, features, and advantages of this disclosure more apparent and understandable, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0049] Because a single unmanned vehicle (UAV) has low operational efficiency when patrolling or cleaning, multiple UAVs are usually required to work together to improve efficiency. Therefore, this disclosure provides a control method, apparatus, device, and storage medium to control multiple UAVs working together in the same area and ensure their operational efficiency. The control provided by this disclosure can be applied to any electronic device capable of data processing and automatic control, including but not limited to computers, mobile phones, and tablets.

[0050] The technical solutions of the embodiments of this disclosure will now be described with reference to the accompanying drawings.

[0051] Figure 1 A schematic flowchart of a control method provided in an embodiment of this disclosure is shown, such as... Figure 1 As shown, the method includes:

[0052] S101, Obtain the target region and divide the target region into multiple corresponding sub-regions.

[0053] In one possible implementation, acquiring the target region may include steps A1-A2:

[0054] Step A1: Determine the obstacle area where the obstacle target is located within the specified area.

[0055] In this disclosure, the designated area can be specifically set according to the application scenario. For example, the area where residential community A is located can be set as the designated area, or the area where school B is located can be set as the designated area.

[0056] Obstacles refer to objects that can affect the driving of autonomous vehicles, such as large buildings or roadblocks.

[0057] Step A2: The area obtained after removing the obstacle area from the specified area is determined as the target area.

[0058] In this disclosure, other areas outside the designated area that do not contain obstacle areas can be used as the target area. Autonomous vehicles can operate within the target area.

[0059] In this disclosure, preferably, the target area can be evenly divided into multiple sub-regions. The number of sub-regions can be specifically set according to the actual application scenario, for example, it can be set to 9 or 12, etc. Alternatively, multiple sub-regions of different sizes can also be used. Specifically, the sub-regions can be divided according to the turning radius of the vehicle-to-everything (V2X) vehicle. For example, the target area can be divided into multiple square sub-regions by using twice the turning radius of the V2X vehicle as the side length of the sub-region.

[0060] S102, obtain access intensity information of each unmanned vehicle for the multiple sub-regions, and determine at least one sub-region corresponding to each unmanned vehicle based on the access intensity information.

[0061] In this disclosure, access intensity information is used to reflect the frequency and duration of unmanned vehicles' access to an area.

[0062] S103, for each unmanned vehicle, determine the target driving path corresponding to the unmanned vehicle based on the specified location information of each sub-region corresponding to the unmanned vehicle.

[0063] This method involves acquiring a target area and dividing it into multiple sub-regions; obtaining access intensity information for each unmanned vehicle (UAV) within these sub-regions; and determining at least one sub-region for each UAV based on this access intensity information. For each UAV, the target driving path is determined according to the specified location information of each sub-region. In other words, by using the access intensity information of each UAV within multiple sub-regions, control is achieved over multiple UAVs operating in the same area, ensuring the operational efficiency of the UAVs.

[0064] In one possible implementation, Figure 2 This illustration shows a flowchart of a process for determining the area corresponding to an unmanned vehicle, as provided in an embodiment of this disclosure. Figure 2 As shown, the step of obtaining access intensity information for each unmanned vehicle to the plurality of sub-regions, and determining at least one sub-region corresponding to each unmanned vehicle based on the access intensity information, includes:

[0065] S201, when entering the cycle, obtain the area division information corresponding to each unmanned vehicle and the access intensity information of each unmanned vehicle for each sub-area.

[0066] The region division information is used to characterize the area occupied by the autonomous vehicle in the target region. The area occupied by the autonomous vehicle in the target region is the area composed of the various sub-regions occupied by the autonomous vehicle in the target region. For example, if target region A includes nine sub-regions, such as sub-region 1 to sub-region 9, and autonomous vehicle B1 occupies sub-region 1 and sub-region 2, and autonomous vehicle B2 occupies sub-regions 3 to 9, then the region division information corresponding to autonomous vehicle B1 can be determined as: sub-region 1 and sub-region 2, and the region division information corresponding to autonomous vehicle B2 is: sub-region 3 to sub-region 9. Specifically, the area occupied by autonomous vehicle B1 is the area composed of sub-region 1 and sub-region 2, and the area occupied by autonomous vehicle B2 is the area composed of sub-regions 3 to 9.

[0067] In this disclosure, the cycle period can be specifically set according to the application scenario, such as half an hour or 1 hour.

[0068] The access intensity information of autonomous vehicles for each sub-region can be determined using the following formula:

[0069] y(i,j)=ex

[0070] Among them, y (i，j) Let x represent the access intensity of autonomous vehicle i to sub-region j, and x be the corresponding access intensity count.

[0071] For driverless car i, when it is detected that driverless car i has accessed sub-region j in the target area, the access intensity count x in the access intensity information corresponding to sub-region j is set to 0, and the ID of sub-region j is marked as the ID of driverless car i; when it is detected that other driverless cars have accessed other sub-regions, the access intensity count x is incremented by 1, and when other driverless cars have accessed sub-region j, x is set back to 0, and the ID of sub-region j is marked as the ID of the driverless car that has recently accessed sub-region j.

[0072] S202, based on the area division information and the access intensity information, determine the occupation status information of each unmanned vehicle in the target area, as well as the first access intensity and the second access intensity corresponding to each unmanned vehicle.

[0073] The first access intensity corresponding to the autonomous vehicle is the minimum access intensity of each sub-region occupied by the autonomous vehicle, and the second access intensity is the maximum access intensity of each sub-region occupied by other autonomous vehicles adjacent to the autonomous vehicle.

[0074] In this disclosure, the occupation status information of each unmanned vehicle in the target area refers to the area occupied by each unmanned vehicle in the target area.

[0075] S203, for each unmanned vehicle, if the occupation status information indicates that the area occupied by each unmanned vehicle is the result of uniformly dividing the target area, and the first access intensity corresponding to the unmanned vehicle is greater than the second access intensity, control the unmanned vehicle to access the first target sub-area currently occupied by the unmanned vehicle.

[0076] The first target sub-region is the sub-region with the lowest access intensity among the sub-regions currently occupied by the unmanned vehicle.

[0077] For each autonomous vehicle, if the occupancy status information indicates that the area occupied by each autonomous vehicle is the result of uniformly dividing the target area, and the first access intensity corresponding to the autonomous vehicle is greater than the second access intensity, it means that the target area is currently uniformly divided by each autonomous vehicle, and there are no abnormal autonomous vehicles around the autonomous vehicle. Therefore, the autonomous vehicle can be controlled to continue to access the sub-area it occupies in the current cycle, so as to obtain more accurate data for determining the corresponding target path in the future.

[0078] For example, suppose the target area C includes four sub-areas, sub-areas 1 through 4, with each sub-area having an equal area. For driverless car D1, if driverless car D1 occupies sub-areas 1 and 2, and driverless car D2 occupies sub-areas 3 and 4, then the areas occupied by driverless cars D1 and D2 represent the result of a uniform division of the target area. Furthermore, driverless car D1 has an access intensity of 0.5 in its occupied sub-area 1 and 1 in its occupied sub-area 2. Adjacent to driverless car D1, driverless car D2 has an access intensity of 0.3 in its occupied sub-area 3 and 0.4 in its occupied sub-area 2. Since the first access intensity for driverless car D1 is greater than the second access intensity, it can be determined that the target area is currently uniformly divided by the driverless cars. Moreover, there are no malfunctioning driverless cars around driverless car D1. Therefore, driverless car D1 can be controlled to access the sub-area with the lowest access intensity currently occupied by it, i.e., it can access sub-area 1.

[0079] S204, if the occupancy status information indicates that the area occupied by each unmanned vehicle is not the result of uniformly dividing the target area, and the first access intensity corresponding to the unmanned vehicle is greater than the second access intensity, control the unmanned vehicle to access the second target sub-area.

[0080] The second target sub-region is the sub-region occupied by the autonomous vehicle with the largest area among the autonomous vehicles adjacent to the autonomous vehicle.

[0081] For each autonomous vehicle, if the occupancy status information indicates that the area occupied by each autonomous vehicle is not the result of uniformly dividing the target area, and the first access intensity corresponding to the autonomous vehicle is greater than the second access intensity, and there are no abnormal autonomous vehicles around the autonomous vehicle, but the target area is not currently uniformly divided by each autonomous vehicle, then in order to make the target area uniformly divided by each autonomous vehicle, the autonomous vehicle can be controlled to access the sub-areas occupied by other autonomous vehicles in the current cycle. Specifically, the autonomous vehicle can be controlled to access the second target sub-area in the current cycle. The second target sub-area can be the sub-area occupied by the autonomous vehicle with the largest corresponding occupied area among the autonomous vehicles adjacent to the autonomous vehicle. The sub-area occupied by the autonomous vehicle with the largest corresponding occupied area can be any sub-area among the sub-areas occupied by the autonomous vehicle with the largest occupied area, or it can be the sub-area with the highest corresponding access intensity among the sub-areas occupied by the autonomous vehicle with the largest occupied area.

[0082] For example, suppose the target area E includes four sub-areas, namely sub-area 1 to sub-area 4, and each sub-area has an equal area. For driverless car F1, if driverless car F1 occupies sub-area 1, and driverless car F2 occupies sub-area 2, sub-area 3, and sub-area 4, then the areas occupied by driverless car F1 and driverless car F2 are not the result of uniformly dividing the target area. Furthermore, the access intensity of driverless car F1 in its occupied sub-region 1 is 1, while the access intensity of driverless car F2, which is adjacent to driverless car F1, is 0.3 in its occupied sub-region 2, 0.5 in its occupied sub-region 3, and 0.8 in its occupied sub-region 2. That is, the first access intensity corresponding to driverless car F1 is greater than the second access intensity, so it can be determined that the target area is not currently uniformly divided by the driverless cars. In addition, there are no abnormal driverless cars around driverless car F1. Therefore, in order to make the target area uniformly divided, driverless car F1 can be controlled to access the second target sub-region. The second target sub-region can be a sub-region of driverless car F2 adjacent to driverless car F1. Specifically, driverless car F1 can access any sub-region occupied by driverless car F2, or it can access the sub-region with the highest access intensity of driverless car F2 corresponding to the sub-region occupied by driverless car F2.

[0083] S205, if the first access intensity corresponding to the unmanned vehicle is not greater than the second access intensity, control the unmanned vehicle to access the third target sub-region.

[0084] The third target sub-region is the sub-region occupied by an autonomous vehicle adjacent to the current autonomous vehicle. Specifically, the third target sub-region can be any sub-region among the sub-regions occupied by any autonomous vehicle adjacent to the current autonomous vehicle, or it can be the sub-region with the highest access intensity among the sub-regions occupied by any autonomous vehicle adjacent to the current autonomous vehicle.

[0085] S206, at the end of the cycle, determine whether the target area has been uniformly divided.

[0086] At the end of the cycle, if all sub-regions of the target area are occupied by autonomous vehicles and each autonomous vehicle occupies the same number of sub-regions, it indicates that the target area has been evenly divided; otherwise, it indicates that the target area has not been evenly divided.

[0087] S207, if so, determine the unmanned vehicle information to which each sub-region belongs and the access intensity information corresponding to each sub-region, and obtain at least one sub-region corresponding to each unmanned vehicle.

[0088] Specifically, the ID of each sub-region can be marked as the ID of the unmanned vehicle occupying that sub-region. The access strength of the unmanned vehicle to the sub-region and the ID of the sub-region are used together as the identifier of the sub-region. The identifier of the sub-region is associated with the unmanned vehicle occupying the sub-region to obtain the corresponding information between each unmanned vehicle and the sub-region.

[0089] S208, if not, when entering the next cycle, return to the step of obtaining the area division information corresponding to each unmanned vehicle and the access intensity information of each unmanned vehicle for each sub-area.

[0090] In this disclosure, after determining at least one sub-region corresponding to each of the unmanned vehicles, the control method may further include steps B1-B2:

[0091] Step B1: Detect whether the area occupied by each unmanned vehicle in the target area has changed.

[0092] When there is a malfunction of an autonomous vehicle or a new autonomous vehicle joins, the area occupied by the autonomous vehicle may change. In this case, in order to ensure that the target area is evenly divided into the areas occupied by each autonomous vehicle, it is necessary to redetermine the sub-area corresponding to each autonomous vehicle.

[0093] Step B2: If yes, redetermine at least one sub-region corresponding to each autonomous vehicle.

[0094] Specifically, the method described in steps 201-208 above can be used to redetermine the sub-regions corresponding to each unmanned vehicle.

[0095] This method utilizes the access intensity information of each autonomous vehicle (RV) to multiple sub-regions to control multiple RVs operating in the same area, ensuring the operational efficiency of the RVs. Furthermore, by controlling the RVs' access to sub-regions of the target area, the size of the area occupied by each RV in the target area can be changed in real time, ensuring that the target area is evenly occupied by RVs. This evens out the area occupied by each RV, improving their collaborative capabilities and further enhancing their operational efficiency.

[0096] In one possible implementation, the designated location information of the sub-region is the center location of the sub-region. For each autonomous vehicle, determining the target driving path corresponding to that autonomous vehicle based on the designated location information of each sub-region may include steps C1-C3:

[0097] Step C1: For each autonomous vehicle, divide the sub-regions occupied by the autonomous vehicle into at least two grids, and determine the center of each grid as the first center position.

[0098] In this disclosure, for each unmanned vehicle, four sub-regions sharing the same vertex in the various sub-regions occupied by the unmanned vehicle can be divided into the same grid, resulting in multiple grids corresponding to the unmanned vehicle, and the center position of the grid is determined as the first center position.

[0099] Step C2: Determine the main path based on the first center location.

[0100] Specifically, starting from the first center position of the edge grid, connect the first center positions of other grids to obtain the longest non-closed path. For the first center positions of other grids not connected into this path, connect the first center position in the middle of this path to the first center position to obtain one or more other paths. All the obtained paths are used as main paths. The main path satisfies the condition that the path line is perpendicular or parallel to the edges of each grid.

[0101] Step C3: Determine the target driving path of the autonomous vehicle by the path formed by the center position of each sub-area occupied by the autonomous vehicle around the main path.

[0102] In this disclosure, the center position of each sub-region occupied by the autonomous vehicle can be used as the second center position. Specifically, starting from any second center position next to a vertex of the main path, other second center positions can be connected along the main path to obtain a closed path, which serves as the target driving path for the autonomous vehicle.

[0103] This method utilizes the access intensity information of each autonomous vehicle (RV) to multiple sub-regions to control multiple RVs operating in the same area, ensuring the operational efficiency of the RVs. Furthermore, by controlling the RVs' access to sub-regions of the target area, the size of the area occupied by each RV in the target area can be changed in real time, ensuring that the target area is evenly occupied by RVs. This evens out the area occupied by each RV, improving their collaborative capabilities and further enhancing their operational efficiency.

[0104] Based on the same inventive concept, and according to the control method provided in the above embodiments of this disclosure, another embodiment of this disclosure also provides a control device, the structural schematic diagram of which is shown below. Figure 3 As shown, it specifically includes:

[0105] The region division module 301 is used to obtain the target region and divide the target region into multiple corresponding sub-regions;

[0106] The sub-region determination module 302 is used to obtain access intensity information of each unmanned vehicle for the multiple sub-regions, and determine at least one sub-region corresponding to each unmanned vehicle based on the access intensity information;

[0107] The path determination module 303 is used to determine the target driving path for each unmanned vehicle based on the specified location information of each sub-region corresponding to the unmanned vehicle.

[0108] This device acquires a target area and divides it into multiple sub-regions. It then acquires access intensity information for each unmanned vehicle (UAV) within these sub-regions and determines at least one sub-region corresponding to each UAV based on this access intensity information. For each UAV, the target driving path is determined according to the specified location information of each sub-region. In other words, by using the access intensity information of each UAV within multiple sub-regions, control is achieved over multiple UAVs operating in the same area, ensuring the operational efficiency of the UAVs.

[0109] In one possible implementation, the region division module 301 is specifically used to determine the obstacle region where the obstacle target is located in the specified region; and to determine the region obtained after removing the obstacle region from the specified region as the target region.

[0110] In one possible implementation, the sub-region determination module 302 is specifically used to, upon entering a loop cycle, acquire region division information corresponding to each unmanned vehicle and access intensity information of each unmanned vehicle for each sub-region. The region division information is used to characterize the region occupied by the unmanned vehicle in the target region, and the region occupied by the unmanned vehicle in the target region is the region composed of the various sub-regions occupied by the unmanned vehicle in the target region. Based on the region division information and the access intensity information, determine the occupation status information of each unmanned vehicle in the target region, as well as the first access intensity and the second access intensity corresponding to each unmanned vehicle. The first access intensity corresponding to the unmanned vehicle is the minimum access intensity of the unmanned vehicle for the various sub-regions it occupies, and the second access intensity is the maximum access intensity of other unmanned vehicles adjacent to the unmanned vehicle for the various sub-regions it occupies. For each unmanned vehicle, if the occupation status information indicates that the region occupied by each unmanned vehicle is the result of uniformly dividing the target region, and the first access intensity corresponding to the unmanned vehicle is greater than the second access intensity, control the unmanned vehicle to access the first target region currently occupied by the unmanned vehicle. The first target sub-region is the sub-region with the lowest access intensity among the sub-regions currently occupied by the autonomous vehicle. If the occupancy status information indicates that the area occupied by each autonomous vehicle is not the result of uniform division of the target region, and the first access intensity corresponding to the autonomous vehicle is greater than the second access intensity, the autonomous vehicle is controlled to access the second target sub-region, which is the sub-region occupied by the autonomous vehicle with the largest area among the autonomous vehicles adjacent to the autonomous vehicle. If the first access intensity corresponding to the autonomous vehicle is not greater than the second access intensity, the autonomous vehicle is controlled to access the third target sub-region, which is the sub-region occupied by the autonomous vehicle adjacent to the autonomous vehicle. At the end of the cycle, it is determined whether the target region is uniformly divided. If yes, the autonomous vehicle information to which each sub-region belongs and the access intensity information corresponding to each sub-region are determined to obtain at least one sub-region corresponding to each autonomous vehicle. If no, when entering the next cycle, the step of obtaining the region division information corresponding to each autonomous vehicle and the access intensity information of each autonomous vehicle for each sub-region is returned.

[0111] In one possible implementation, the designated location information of the sub-region is the center location of the sub-region; the path determination module 303 is specifically used to divide each sub-region occupied by the unmanned vehicle into at least two grids for each unmanned vehicle, and determine the center of each grid as the first center location; determine the main path based on the first center location; and determine the path formed by the center locations of each sub-region occupied by the unmanned vehicle around the main path as the target driving path corresponding to the unmanned vehicle.

[0112] In one embodiment, the sub-region determination module 302 is further configured to detect whether the area occupied by each unmanned vehicle in the target area has changed; if so, to redetermine at least one sub-region corresponding to each unmanned vehicle.

[0113] This device enables control of multiple unmanned vehicles (UAVs) operating in the same area by leveraging the access intensity information of each UAV to multiple sub-regions, thus ensuring the operational efficiency of the UAVs. Furthermore, by controlling the UAVs' access to sub-regions of the target area, the size of the area occupied by each UAV within the target area can be changed in real time, ensuring that the target area is evenly occupied by the UAVs. This evenness in the area occupied by each UAV improves their collaborative capabilities and further enhances their operational efficiency.

[0114] According to embodiments of this disclosure, this disclosure also provides an electronic device and a readable storage medium.

[0115] Figure 4 A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0116] like Figure 4 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 402 or a computer program loaded from storage unit 408 into random access memory (RAM) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0117] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0118] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as control methods. For example, in some embodiments, the control method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the control method described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform control methods by any other suitable means (e.g., by means of firmware).

[0119] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0120] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0121] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0122] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0123] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0124] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0125] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0126] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise explicitly specified.

[0127] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A control method, characterized in that, The method includes: Obtain the target region and divide it into multiple corresponding sub-regions; Obtain access intensity information for each unmanned vehicle for the multiple sub-regions, and determine at least one sub-region corresponding to each unmanned vehicle based on the access intensity information; For each autonomous vehicle, the target driving path is determined based on the specified location information of each sub-region corresponding to that autonomous vehicle. The step of obtaining access intensity information for each autonomous vehicle to the plurality of sub-regions, and determining at least one sub-region corresponding to each autonomous vehicle based on the access intensity information, includes: When entering the loop cycle, the region division information corresponding to each unmanned vehicle and the access intensity information of each unmanned vehicle for each sub-region are obtained. The region division information is used to characterize the area occupied by the unmanned vehicle in the target area. The area occupied by the unmanned vehicle in the target area is the area composed of the various sub-regions occupied by the unmanned vehicle in the target area. Based on the area division information and the access intensity information, determine the occupation status information of each unmanned vehicle in the target area, as well as the first access intensity and the second access intensity corresponding to each unmanned vehicle. The first access intensity corresponding to the unmanned vehicle is the minimum access intensity of the unmanned vehicle in each sub-area it occupies, and the second access intensity is the maximum access intensity of other unmanned vehicles adjacent to the unmanned vehicle in each sub-area it occupies. For each autonomous vehicle, if the occupation status information indicates that the area occupied by each autonomous vehicle is the result of uniformly dividing the target area, and the first access intensity corresponding to the autonomous vehicle is greater than the second access intensity, the autonomous vehicle is controlled to access the first target sub-region currently occupied by the autonomous vehicle. The first target sub-region is the sub-region with the lowest access intensity among the sub-regions currently occupied by the autonomous vehicle. If the occupation status information indicates that the area occupied by each unmanned vehicle is not the result of uniformly dividing the target area, and the first access intensity corresponding to the unmanned vehicle is greater than the second access intensity, the unmanned vehicle is controlled to access the second target sub-region. The second target sub-region is the sub-region occupied by the unmanned vehicle with the largest occupied area among the unmanned vehicles adjacent to the unmanned vehicle. If the first access intensity corresponding to the unmanned vehicle is not greater than the second access intensity, control the unmanned vehicle to access the third target sub-region, the third target sub-region being the sub-region occupied by the unmanned vehicle adjacent to the unmanned vehicle; At the end of the cycle, it is determined whether the target region has been uniformly divided. If so, determine the unmanned vehicle information to which each sub-region belongs and the access intensity information corresponding to each sub-region, and obtain at least one sub-region corresponding to each unmanned vehicle; If not, when entering the next cycle, return to the steps of obtaining the area division information corresponding to each unmanned vehicle and the access intensity information of each unmanned vehicle for each sub-area.

2. The method according to claim 1, characterized in that, The acquisition of the target area includes: Determine the obstacle area where the obstacle target is located within the specified area; The area obtained after removing the obstacle area from the specified area is determined as the target area.

3. The method according to claim 1, characterized in that, The specified location information for a sub-region is its center location. For each autonomous vehicle, determining the target driving path corresponding to that vehicle based on the specified location information of each sub-region includes: For each autonomous vehicle, the sub-regions occupied by the autonomous vehicle are divided into at least two grids, and the center of each grid is determined as the first center position; The main path is determined based on the first center location; The center position of each sub-region occupied by the autonomous vehicle is determined by the path formed around the main path as the target driving path of the autonomous vehicle.

4. The method according to claims 1-2, characterized in that, The method further includes: Detect whether the area occupied by each unmanned vehicle within the target area has changed; If so, redetermine at least one sub-region corresponding to each autonomous vehicle.

5. A control device, characterized in that, The device includes: The region division module is used to obtain the target region and divide the target region into multiple corresponding sub-regions; The sub-region determination module is used to obtain access intensity information of each unmanned vehicle for the multiple sub-regions, and determine at least one sub-region corresponding to each unmanned vehicle based on the access intensity information. The path determination module is used to determine the target driving path for each autonomous vehicle based on the specified location information of each sub-region corresponding to the autonomous vehicle. Specifically, the sub-region determination module is used to acquire, upon entering a loop cycle, the region division information corresponding to each autonomous vehicle and the access intensity information of each autonomous vehicle for each sub-region. The region division information is used to characterize the area occupied by each autonomous vehicle in the target area, and the area occupied by each autonomous vehicle in the target area is the area composed of the various sub-regions occupied by each autonomous vehicle in the target area. Based on the region division information and the access intensity information, the module determines the occupancy status information of each autonomous vehicle in the target area, as well as the first access intensity and the second access intensity corresponding to each autonomous vehicle. The first access intensity corresponding to each autonomous vehicle is the minimum access intensity of the autonomous vehicle for the various sub-regions it occupies, and the second access intensity is the maximum access intensity of other autonomous vehicles adjacent to the autonomous vehicle for the various sub-regions it occupies. For each autonomous vehicle, if the occupancy status information indicates that the area occupied by each autonomous vehicle is the result of uniformly dividing the target area, and the first access intensity corresponding to the autonomous vehicle is greater than the second access intensity, the module controls the autonomous vehicle to access the first target sub-region currently occupied by the autonomous vehicle. The first target sub-region is the sub-region with the lowest access intensity among the sub-regions currently occupied by the autonomous vehicle. If the occupancy status information indicates that the area occupied by each autonomous vehicle is not the result of uniform division of the target region, and the first access intensity corresponding to the autonomous vehicle is greater than the second access intensity, the autonomous vehicle is controlled to access the second target sub-region, which is the sub-region occupied by the autonomous vehicle with the largest corresponding area among the autonomous vehicles adjacent to the autonomous vehicle. If the first access intensity corresponding to the autonomous vehicle is not greater than the second access intensity, the autonomous vehicle is controlled to access the third target sub-region, which is the sub-region occupied by the autonomous vehicles adjacent to the autonomous vehicle. At the end of the cycle, it is determined whether the target region is uniformly divided. If yes, the autonomous vehicle information to which each sub-region belongs and the access intensity information corresponding to each sub-region are determined to obtain at least one sub-region corresponding to each autonomous vehicle. If no, when entering the next cycle, the step of obtaining the region division information corresponding to each autonomous vehicle and the access intensity information of each autonomous vehicle for each sub-region is returned.

6. The apparatus according to claim 5, characterized in that, The region division module is specifically used to determine the obstacle region where the obstacle target is located in the specified region; and to determine the region obtained after removing the obstacle region from the specified region as the target region.

7. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.

8. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-4.

Images