A transport robot path planning system for new energy charging parking lots

Abstract

The present invention discloses a transport robot path planning system for a new energy charging parking lot. The transport robot path planning system for a new energy charging parking lot includes: a garage data acquisition module, an information interaction module, a central control module, and an AGV transport robot. The present invention obtains the vehicle energy drive mode through the garage data acquisition module, sends an energy replenishment prompt to the user through the information interaction module, and obtains the user confirmation signal. If confirmed, the central control module allocates a parking space according to the garage data and the energy drive mode, and uses the A* algorithm to plan the transport path, and transmits the transport path information to the AGV transport robot, which accurately transports the vehicle to the allocated parking space, thereby improving the user experience and solving the current problem of poor user experience.

Description

Technical Field

[0001] The present invention relates to the technical field of charging parking lots, and in particular to a transport robot path planning system for a new energy charging parking lot. Background Art

[0002] New energy charging parking lots are important facilities for the automotive industry's transition to clean energy, and are used to provide charging services for electric vehicles. With the development of artificial intelligence and machine learning technologies, some parking lots have begun to use intelligent methods to allocate parking spaces. These methods can dynamically adjust parking space allocation strategies based on real-time data such as traffic flow and charging demand, and reasonable parking space allocation can directly affect the path optimization of the handling robot, thereby improving the efficiency of the entire parking system.

[0003] At present, traditional parking space allocation methods are usually based on static planning and cannot fully adapt to the real-time changes in parking lots, which leads to insufficient parking space utilization and inflexibility in path planning of handling robots.

[0004] For example, the emergency communication drone system and emergency communication system disclosed in the publication number CN109801484A include: integrating POS, DSM and vector data, using 3D modeling of dense image matching to automatically generate dense point cloud data of objects, and quickly creating large-scale 3D models through automatic texture mapping, which has a strong sense of reality and reduces the cost of project implementation. The obstacle avoidance module has the characteristics of accurate measurement, high degree of automation, safety and reliability, and easy use; at the same time, the communication path planning module has good real-time and rapidity, so that the drone can search for tracks closer to the actual optimal track of the drone when performing tasks such as emergency communication and air rescue.

[0005] For example, a GPS-positioned meter reading smart handheld device and a meter reading system disclosed in Publication No. CN103927860A include: multiple smart handheld devices receive meter reading tasks issued by a background server, and plan meter reading routes according to the meter reading tasks; during the meter reading process, the GPS position coordinates of the handheld devices are uploaded to the background of the meter reading system in real time, and the meter reading data is uploaded to the background server; the background server downloads the meter reading tasks to the smart handheld devices according to the geographical location, can monitor the GPS position of each handheld device in real time, receive and store the meter reading data uploaded by the handheld device; the real-time position information of each smart handheld device can be queried on a map to reproduce the actual operation path of the terminal.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] At present, the parking spaces in the new energy charging parking lot are full, but the movable charging piles are not fully utilized. At the same time, it is difficult to determine whether the stored vehicles can be replenished in time, resulting in problems such as the vehicle not being charged when the user picks up the vehicle, which seriously reduces the user experience and leads to poor user experience. Summary of the invention

[0008] The embodiment of the present application solves the problem of poor user experience in the prior art by providing a transport robot path planning system for a new energy charging parking lot, thereby effectively improving the user experience.

[0009] An embodiment of the present application provides a transport robot path planning system for a new energy charging parking lot, comprising: a garage data acquisition module, an information interaction module, a central control module, and an AGV transport robot; wherein the garage data acquisition module is used to obtain the garage data of the current new energy charging parking lot; the information interaction module is used to visually display charging prompt information to the user and obtain the user's charging selection information; the central control module is used to obtain the current garage data, charging prompt information, and charging selection information, and plan the transport path information of the AGV transport robot based on the A* algorithm; the AGV transport robot is used to obtain the transport path information and complete the transport task based on it.

[0010] Furthermore, the garage data acquisition module includes a driving energy identification unit, a charging pile information acquisition unit and a garage data acquisition unit; the driving energy identification unit is used to obtain the vehicle identification information of the user's vehicle to be stored, and derive the energy driving mode of the vehicle to be stored according to the vehicle identification information; the charging pile information acquisition unit is used to obtain the charging pile information in the new energy charging parking lot, and the charging pile information includes the charging pile location information, the charging pile working status information, and the charging power of the charging pile; the garage data acquisition unit is used to obtain the garage data of the new energy charging parking lot, and the garage data includes parking room data, parking space data and AGV transport robot data.

[0011] Furthermore, the garage data includes parking room data, parking space data and AGV transport robot data; the parking room data includes parking room location data and parking room vacancy data; the parking space data includes parking space location data, parking space vacancy data, and charging pile location information; the AGV transport robot data includes real-time location data and real-time task status data.

[0012] Furthermore, the information interaction module includes an energy replenishment time analysis unit, an information prompt visualization unit and a user selection acquisition unit; the energy replenishment time analysis unit is used to obtain an estimated charging amount based on the total energy amount of the user's vehicle to be stored, and to obtain an estimated charging time for the vehicle to be stored based on the charging power of the charging pile; the information prompt visualization unit is used to visualize the estimated charging time and the estimated charging amount to the user; the user selection acquisition unit is used to obtain the total energy amount of the vehicle to be stored input by the user, and is also used to obtain a charging confirmation signal input by the user.

[0013] Furthermore, the central control module includes a parking space allocation unit, an information transmission unit and a route planning unit; the parking space allocation unit is used to determine whether the new energy charging parking lot can replenish energy for the vehicles to be stored according to the first allocation constraint condition. If not, charging piles will not be allocated to the vehicles to be stored. If so, charging piles will be allocated to the vehicles to be stored. The unit is also used to allocate parking spaces to the vehicles to be stored after comprehensive analysis of the energy driving mode and charging pile information of the vehicles to be stored; the information transmission unit is used to obtain the energy driving mode and charging pile information of the vehicles to be stored from the garage data acquisition module, and send the transport path information to the AGV transport robot; the route planning unit is used to analyze the transport path information based on the parking space allocated to the vehicles to be stored and the AGV transport robot data.

[0014] Furthermore, the first allocation constraint condition is: Wherein, F1 is the first allocation constraint, F1=0 means that energy cannot be replenished for the vehicles to be stored, F2 is the second allocation constraint, F1=F2 means that energy is replenished for the vehicles to be stored according to the second allocation constraint, DK is the number of idle charging piles, WK is the number of idle parking spaces, EN is the energy driving mode of the vehicles to be stored, EN=1 means that the energy driving mode of the vehicles to be stored is electric energy replenishment mode; the second allocation constraint is: In the formula, F2=1 indicates that energy can be replenished for the waiting vehicle, G1 is the available index of the charging pile, G2 is the available index of the parking space, F2=G1 indicates that energy is replenished for the waiting vehicle according to the available index of the charging pile, and F2=G2 indicates that energy is replenished for the waiting vehicle according to the available index of the parking space; when the available index G1 of the charging pile is greater than a certain threshold, it indicates that energy can be replenished for the waiting vehicle, otherwise, energy cannot be replenished for the waiting vehicle; when the available index G2 of the parking space is greater than a certain threshold, it indicates that energy can be replenished for the waiting vehicle, otherwise, energy cannot be replenished for the waiting vehicle.

[0015] Further, the specific analysis method for allocating parking spaces for vehicles to be stored after the comprehensive analysis is as follows: all charging piles in the new energy charging parking lot are movable charging piles, and the charging pile positions of the movable charging piles are randomly allocated in the new energy charging parking lot; when it is determined that charging piles are allocated for vehicles to be stored, the garage data in the new energy charging parking lot is obtained; the information of all parked vehicles in the new energy charging parking lot is obtained, and all parked vehicles are numbered; the number of free parking spaces is extracted according to the garage data, and the remaining waiting time for the vehicle to be picked up is extracted according to the information of the parked vehicles; when the number of free parking spaces is 0, the vehicles to be stored whose energy driving mode is not an electric energy replenishment mode are stopped from being received; a parking space availability index analysis formula is constructed, and the parking space availability index is analyzed according to it; the parking space availability indexes greater than a certain threshold are sorted from large to small, and the parking space corresponding to the maximum parking space availability index is allocated to the vehicle to be stored for parking and waiting for energy replenishment; at the same time, the parked vehicle parked in the parking space corresponding to the maximum parking space availability index is moved to the parking room for temporary storage, and all other vehicles are stopped from being received.

[0016] Furthermore, the specific analysis method for allocating charging piles to the vehicles to be stored is as follows: obtain the garage data in the new energy charging parking lot and the charging pile information of all movable charging piles, and number the movable charging piles; obtain the information of all parked vehicles in the new energy charging parking lot, and number the parked vehicles; extract the parked vehicles currently being charged according to the parked vehicle information, and obtain the remaining amount of charge corresponding to the parked vehicles currently being charged and the remaining power of the current movable charging piles; construct a charging pile availability index analysis formula, and analyze the charging pile availability index based on it; sort the charging pile availability indexes greater than a certain threshold from large to small, and allocate the movable charging pile corresponding to the maximum value of the charging pile availability index to the vehicles to be stored for energy replenishment.

[0017] Furthermore, the charging pile can be analyzed by the index formula:

[0018] Where ΔT1 is the maximum allowed waiting time for the charging pile to finish, EC k is the remaining charge capacity of the parked vehicle, k is the number of the currently charged parked vehicle, k = 1, 2, 3, ..., K, K is the total number of currently charged parked vehicles, W is the power of the charging pile, α1 is the weight of the waiting time of the charging pile in the charging pile availability index, ED k→iis the current remaining power of the movable charging pile i corresponding to the parked vehicle k currently being charged, i is the number of the movable charging pile, i=1,2,3,...,I, I is the total number of movable charging piles, when DK=0, the number of movable charging piles I is equal to the number of parked vehicles K currently being charged, wherein i corresponds to k one by one, EYk0 is the estimated charging capacity of the current vehicle k0 to be stored, and α2 is the weight ratio of the remaining power of the movable charging pile that can be replenished by the vehicle to be stored in the charging pile availability index.

[0019] Furthermore, the parking space availability index analysis formula is: G2 = max[(ΔT2-T g )*β1+(N-SK-1)*β2], where ΔT2 is the maximum allowed waiting time for the parking space to end, T g is the remaining waiting time for the parked vehicle, g is the number of all parked vehicles, g = 1, 2, 3, ..., G, G is the total number of all parked vehicles, β1 is the weighted proportion of the parking waiting time in the parking space availability index, N is the total number of parking rooms, SK is the remaining number of vacant parking rooms, and β2 is the weighted proportion of the remaining number of parking rooms in the parking space availability index.

[0020] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0021] 1. Intelligent planning of the charging process is achieved through energy replenishment time analysis, and important information is displayed to users in a visual way, so that users can actively participate in selecting acquisition units, thereby improving the user's charging experience and optimizing the system's operating efficiency. It provides new energy charging parking lots with smarter and more humane services, effectively solving the problem of poor user experience in existing technologies.

[0022] 2. By comprehensively considering the real-time status of charging piles and vehicles, suitable charging piles are intelligently allocated to the vehicles to be stored, and the charging piles are sorted and selected according to their available index, thereby maximizing the utilization rate of charging piles, which in turn helps to optimize the allocation of charging pile resources in new energy charging parking lots and improve the overall parking lot operation efficiency.

[0023] 3. By making rational use of the information of parked vehicles and the number of vacant parking spaces, the system can efficiently allocate charging piles and parking spaces to the vehicles to be stored, thereby minimizing the waste of charging piles and parking spaces, and ensuring that the allocated parking spaces are more reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic diagram of the structure of a transport robot path planning system for a new energy charging parking lot provided in an embodiment of the present application;

[0025] Figure 2 A schematic diagram of the structure of a garage data acquisition module provided in an embodiment of the present application;

[0026] Figure 3 A schematic diagram of the structure of the information interaction module provided in the embodiment of the present application;

[0027] Figure 4 A schematic diagram of the structure of the central control module provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The embodiment of the present application solves the problem of poor user experience in the prior art by providing a transport robot path planning system for new energy charging parking lots, realizes intelligent planning of the charging process through energy replenishment time analysis, and displays important information to users in a visual manner, so that users can actively participate in selecting acquisition units, thereby improving the user's charging experience, optimizing the system's operating efficiency, and providing new energy charging parking lots with smarter and more humane services.

[0029] The technical solution in the embodiment of the present application is to solve the above-mentioned problem of poor user experience, and the overall idea is as follows:

[0030] Before the vehicle enters the parking room, the garage data acquisition module obtains the vehicle identification information, and the energy driving mode of the vehicle is obtained according to the vehicle identification information; the information interaction module sends an energy replenishment prompt to the user according to the energy driving mode, and obtains a confirmation signal or a denial signal of the user's choice to replenish energy for the vehicle; when the information interaction module obtains the user's confirmation signal to replenish energy and the vehicle enters the parking room, the garage data acquisition module obtains the current garage data; the central control module allocates a parking space for the vehicle according to the current garage data and the energy driving mode of the vehicle, and uses the A* algorithm to obtain the transportation path information according to the allocated parking space data of the vehicle, and sends the transportation path information to the AGV transportation robot; the AGV transportation robot receives the transportation path information corresponding to the vehicle, and sends the vehicle to the parking space according to the path, thereby effectively improving the user experience.

[0031] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0032] like Figure 1As shown, it is a structural schematic diagram of the path planning system of the handling robot for the new energy charging parking lot provided in the embodiment of the present application. The path planning system of the handling robot for the new energy charging parking lot provided in the embodiment of the present application includes: a garage data acquisition module, an information interaction module, a central control module, and an AGV handling robot; wherein, the garage data acquisition module is used to obtain the garage data of the current new energy charging parking lot; the information interaction module is used to visually display the charging prompt information to the user and obtain the user's charging selection information; the central control module is used to obtain the current garage data, charging prompt information, and charging selection information, and plan the handling path information of the AGV handling robot according to the A* algorithm; the AGV handling robot is used to obtain the handling path information and complete the handling task accordingly.

[0033] In this embodiment, the A* algorithm is a search algorithm widely used in the field of path planning. Its real-time planning process plays an important role in the path planning system of the handling robot in the new energy charging parking lot. The real-time garage data of the current parking lot is obtained through the garage data acquisition module. The A* algorithm can efficiently search for the shortest path between parking spaces, taking into account the cost and heuristic function of the path to ensure that the AGV handling robot can quickly and accurately reach the target parking space.

[0034] Further, such as Figure 2 As shown, it is a structural schematic diagram of the garage data acquisition module provided in an embodiment of the present application, and the garage data acquisition module includes a driving energy identification unit, a charging pile information acquisition unit and a garage data acquisition unit; the driving energy identification unit is used to obtain the vehicle identification information of the user's vehicle to be stored, and derive the energy driving mode of the vehicle to be stored according to the vehicle identification information; the charging pile information acquisition unit is used to obtain the charging pile information in the new energy charging parking lot, and the charging pile information includes the charging pile location information, the charging pile working status information, and the charging power of the charging pile; the garage data acquisition unit is used to obtain the garage data of the new energy charging parking lot, and the garage data includes parking room data, parking space data and AGV transport robot data.

[0035] In this embodiment, the power of the electric vehicle charging pile depends on its type and level. AC piles generally have two power levels of 3.5kw and 7kw, which are suitable for national standard slow charging ports and are mainly used in places such as residential areas, homes, and shopping mall parking lots to provide slow charging services for new energy electric vehicles. In contrast, DC piles have multiple levels such as 30kw, 60kw, 120kw, and 240kw, which are suitable for fast charging and are widely used in highway service areas and other places. Since the power of AC piles is relatively small and the charging speed is slow, they are suitable for long-term parking scenarios, such as residential and family cars, as well as charging facilities open to the public such as shopping mall parking lots.

[0036] Furthermore, garage data includes parking room data, parking space data and AGV transport robot data; parking room data includes parking room location data and parking room vacancy data; parking space data includes parking space location data, parking space vacancy data, and charging pile location information; AGV transport robot data includes real-time location data and real-time task status data.

[0037] Further, such as Figure 3 As shown, it is a structural schematic diagram of the information interaction module provided in an embodiment of the present application, and the information interaction module includes an energy replenishment time analysis unit, an information prompt visualization unit and a user selection acquisition unit; the energy replenishment time analysis unit is used to obtain an estimated charging amount according to the total energy amount of the vehicle to be stored by the user, and to obtain an estimated charging time of the vehicle to be stored according to the charging power of the charging pile; the information prompt visualization unit is used to visualize the estimated charging time and the estimated charging amount to the user; the user selection acquisition unit is used to obtain the total energy amount of the vehicle to be stored input by the user, and is also used to obtain a charging confirmation signal input by the user.

[0038] In this embodiment, the energy replenishment time analysis unit predicts the charging time of the vehicle to be stored by analyzing the total energy of the user's vehicle to be stored and combining it with the charging power of the charging pile. This enables the system to analyze how long the user is expected to wait before starting charging based on the status of the charging pile and the status of other vehicles being charged. The information prompt visualization unit displays the estimated charging time and the estimated charging amount to the user in a visual manner to improve the user's understanding of the charging process. The user selection acquisition unit is responsible for obtaining the total energy of the vehicle to be stored and the charging confirmation signal input by the user, allowing the user to decide whether to choose to charge.

[0039] Further, such as Figure 4 As shown, it is a structural schematic diagram of the central control module provided in an embodiment of the present application, and the central control module includes a parking space allocation unit, an information transmission unit and a route planning unit; the parking space allocation unit is used to determine whether the new energy charging parking lot can replenish energy for the vehicle to be stored according to the first allocation constraint condition. If not, the charging pile will not be allocated to the vehicle to be stored. If it can, the charging pile will be allocated to the vehicle to be stored. It is also used to allocate parking spaces to the vehicles to be stored after comprehensive analysis of the energy driving mode and charging pile information of the vehicles to be stored; the information transmission unit is used to obtain the energy driving mode and charging pile information of the vehicles to be stored from the garage data acquisition module, and send the transportation path information to the AGV transportation robot; the route planning unit is used to analyze the transportation path information according to the parking space allocated to the vehicle to be stored and the AGV transportation robot data.

[0040] In this embodiment, the central control module plays a key role in the path planning system of the handling robot in the new energy charging parking lot, which is mainly composed of a parking space allocation unit, an information transmission unit and a route planning unit. First, the parking space allocation unit determines whether the new energy charging parking lot can replenish energy for the vehicles to be stored according to the first allocation constraint. If the conditions are met, the charging piles are allocated, and the energy drive mode and charging pile information of the vehicles to be stored are comprehensively considered to allocate suitable charging piles and parking spaces for them. This process effectively avoids the waste of system resources and improves the utilization rate of charging piles and parking spaces. The route planning unit uses the parking space information allocated to the vehicles to be stored and the real-time data of the AGV handling robot to analyze the optimal handling path information through planning algorithms such as the A* algorithm. This process ensures that the robot chooses the shortest and most efficient path when performing tasks, reduces handling time, reduces energy consumption, and improves the efficiency of overall path planning.

[0041] Furthermore, the first allocation constraint is: Where, F1 is the first allocation constraint, F1=0 means that energy cannot be replenished for the vehicles to be stored, F2 is the second allocation constraint, F1=F2 means that energy is replenished for the vehicles to be stored according to the second allocation constraint, DK is the number of idle charging piles, WK is the number of idle parking spaces, EN is the energy driving mode of the vehicles to be stored, EN=1 means that the energy driving mode of the vehicles to be stored is electric energy replenishment; the second allocation constraint is: In the formula, F2=1 indicates that energy can be replenished for the waiting vehicle, G1 is the available index of the charging pile, G2 is the available index of the parking space, F2=G1 indicates that energy is replenished for the waiting vehicle according to the available index of the charging pile, and F2=G2 indicates that energy is replenished for the waiting vehicle according to the available index of the parking space; when the available index G1 of the charging pile is greater than a certain threshold, it indicates that energy can be replenished for the waiting vehicle, otherwise, energy cannot be replenished for the waiting vehicle; when the available index G2 of the parking space is greater than a certain threshold, it indicates that energy can be replenished for the waiting vehicle, otherwise, energy cannot be replenished for the waiting vehicle.

[0042] In this embodiment, the charging pile availability index and the parking space availability index are respectively certain thresholds, and the certain thresholds are both greater than zero.

[0043] Further, after comprehensive analysis, the specific analysis method for allocating parking spaces for vehicles to be stored is as follows: all charging piles in the new energy charging parking lot are movable charging piles, and the charging pile positions of the movable charging piles are randomly allocated in the new energy charging parking lot; when it is determined that charging piles are allocated for vehicles to be stored, the garage data in the new energy charging parking lot is obtained; the information of all parked vehicles in the new energy charging parking lot is obtained, and all parked vehicles are numbered; the number of free parking spaces is extracted according to the garage data, and the remaining waiting time for the vehicle to be picked up is extracted according to the information of the parked vehicles; when the number of free parking spaces is 0, the vehicles to be stored whose energy driving mode is not electric energy replenishment mode are stopped from being accepted; a parking space availability index analysis formula is constructed, and the parking space availability index is analyzed based on it; the parking space availability indexes greater than a certain threshold are sorted from large to small, and the parking space corresponding to the maximum parking space availability index is allocated to the vehicle to be stored for parking and waiting for energy replenishment; at the same time, the parked vehicle parked in the parking space corresponding to the maximum parking space availability index is moved to the parking room for temporary storage, and all other vehicles are stopped from being accepted.

[0044] In this embodiment, the specific analysis method for comprehensively analyzing the allocation of parking spaces for vehicles to be stored includes the following steps: First, the new energy charging parking lot uses movable charging piles, and the positions of the charging piles are randomly allocated in the parking lot, which increases the flexibility and coverage of the charging piles. After determining to allocate charging piles for vehicles to be stored, the garage data in the new energy charging parking lot is obtained to achieve a comprehensive grasp of the charging facilities in the venue. Subsequently, by obtaining the information of parked vehicles and numbering these vehicles, the system can extract the number of free parking rooms according to the garage data, and extract the remaining waiting time for the vehicle to be picked up in combination with the information of the parked vehicles. This step effectively utilizes the existing vehicle information in the parking lot and provides an important reference for the subsequent allocation of parking spaces. When the number of free parking spaces is 0, the system will stop receiving those vehicles to be stored whose energy drive mode is not supplemented by electric energy, thereby avoiding the inability of the allocated charging piles to supplement the energy for the vehicle. Then, by constructing a parking space availability index analysis formula, the system can comprehensively consider factors such as the number of free parking rooms and the remaining waiting time for the vehicle to be picked up, and analyze the parking space availability index. The parking space availability index greater than a certain threshold is sorted, and the parking space corresponding to the maximum parking space availability index is allocated to the waiting vehicle for parking and waiting for energy replenishment. At the same time, the parked vehicle parked in the parking space corresponding to the maximum parking space availability index is moved to the parking room for temporary storage, and all other vehicles are stopped from being accepted. By rationally utilizing the information of parked vehicles and the number of free parking rooms, the system can efficiently allocate charging piles and parking spaces to the waiting vehicles, minimizing the waste of charging piles and parking spaces. The use of movable charging piles also increases the adaptability of charging piles and improves the charging efficiency of parking lots. The entire process ensures that the allocated parking spaces are more reasonable through the sorting and selection of parking space availability indexes, providing users with a more convenient and intelligent charging service experience.

[0045] Furthermore, the specific analysis method for allocating charging piles to the vehicles to be stored is as follows: obtain the garage data in the new energy charging parking lot and the charging pile information of all movable charging piles, and number the movable charging piles; obtain the information of all parked vehicles in the new energy charging parking lot, and number the parked vehicles; extract the parked vehicles currently being charged according to the parked vehicle information, and obtain the remaining amount of charge corresponding to the parked vehicles currently being charged and the remaining power of the current movable charging piles; construct a charging pile availability index analysis formula, and analyze the charging pile availability index based on it; sort the charging pile availability indexes greater than a certain threshold from large to small, and allocate the movable charging pile corresponding to the maximum value of the charging pile availability index to the vehicles to be stored for energy replenishment.

[0046] In this embodiment, the specific analysis method for allocating charging piles to the vehicles to be stored includes the following steps: First, by obtaining the garage data in the new energy charging parking lot, all the movable charging piles are numbered, and their charging pile information, including location, working status, etc., is obtained. This process ensures that the system has a comprehensive understanding of the distribution and status of the charging piles. At the same time, the information of the parked vehicles is obtained, and these vehicles are numbered to provide the necessary data basis for subsequent analysis. Next, the currently charged parked vehicles are extracted according to the parked vehicle information, and their remaining to-be-charged amount and the remaining power of the current movable charging pile are obtained. This step realizes real-time monitoring of the status of the charging vehicles and charging piles, and provides key data for the subsequent construction of the charging pile availability index. Subsequently, by constructing the charging pile availability index analysis formula, the system can comprehensively consider factors such as the information of the currently charged vehicle and the remaining power of the movable charging pile, and analyze the charging pile availability index. The charging pile availability index greater than a certain threshold is sorted from large to small, and the movable charging pile corresponding to the maximum value of the charging pile availability index is selected, and it is allocated to the vehicle to be stored for energy replenishment. This process realizes the intelligent allocation of movable charging piles and ensures the efficient use of charging piles. By comprehensively considering the real-time status of charging piles and vehicles, suitable charging piles are intelligently allocated to the vehicles to be stored. By sorting and selecting the charging pile availability index, the system maximizes the utilization rate of charging piles and provides users with a more efficient and intelligent charging service experience. This analysis method helps to optimize the allocation of charging pile resources in new energy charging parking lots and improve the overall parking lot operation efficiency.

[0047] Furthermore, the charging pile usable index analysis formula is:

[0048] Where ΔT1 is the maximum allowed waiting time for the charging pile to finish, EC k is the remaining charge capacity of the parked vehicle, k is the number of the currently charged parked vehicle, k = 1, 2, 3, ..., K, K is the total number of currently charged parked vehicles, W is the power of the charging pile, α1 is the weight of the waiting time of the charging pile in the charging pile availability index, ED k→i is the current remaining power of the movable charging pile i corresponding to the parked vehicle k currently being charged, i is the number of the movable charging pile, i=1,2,3,...,I, I is the total number of movable charging piles, when DK=0, the number of movable charging piles I is equal to the number of parked vehicles K currently being charged, wherein i corresponds to k one by one, EYk0 is the estimated charging capacity of the current vehicle k0 to be stored, and α2 is the weight ratio of the remaining power of the movable charging pile that can be replenished by the vehicle to be stored in the charging pile availability index.

[0049] In this embodiment, in the charging pile availability index analysis formula, and Both must be greater than zero, otherwise the calculated result will be invalid and will not be included in the sorting.

[0050] Furthermore, the parking space availability index analysis formula is: G2 = max[(ΔT2-T g )*β1+(N-SK-1)*β2], where ΔT2 is the maximum allowed waiting time for the parking space to end, T g is the remaining waiting time for the parked vehicle, g is the number of all parked vehicles, g = 1, 2, 3, ..., G, G is the total number of all parked vehicles, β1 is the weighted proportion of the parking waiting time in the parking space availability index, N is the total number of parking rooms, SK is the remaining number of vacant parking rooms, and β2 is the weighted proportion of the remaining number of parking rooms in the parking space availability index.

[0051] In this embodiment, in the parking space availability index analysis formula, ΔT2-T g and N-SK-1 must both be greater than zero, otherwise the calculated result is invalid and will not be included in the ranking.

[0052] The technical scheme in the above-mentioned embodiment of the present application has at least the following technical effects or advantages: relative to an emergency communication drone system and an emergency communication system disclosed in publication number: CN109801484A, the embodiment of the present application realizes intelligent planning of the charging process through energy replenishment time analysis, and also displays important information to the user in a visual manner, so that the user selects the acquisition unit to realize the user's active participation, thereby improving the user's charging experience, and optimizing the system's operating efficiency, providing a smarter and more humane service for the new energy charging parking lot; relative to a GPS positioning meter reading smart handheld and meter reading system disclosed in publication number: CN103927860A, the embodiment of the present application comprehensively considers the real-time status of the charging piles and the vehicles, and intelligently allocates suitable charging piles to the vehicles to be stored, and sorts and selects the available index of the charging piles, thereby maximizing the utilization rate of the charging piles, thereby helping to optimize the allocation of charging pile resources in the new energy charging parking lot and improve the overall parking lot operation efficiency.

[0053] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0054] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0055] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0056] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0057] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0058] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A transport robot path planning system for a new energy charging parking lot, characterized in that: include: Garage data acquisition module, information interaction module, central control module, AGV handling robot; Wherein, the garage data acquisition module is used to acquire the garage data of the current new energy charging parking lot; The information interaction module is used to visually display charging prompt information to the user and obtain the user's charging selection information; The central control module is used to obtain current garage data, charging prompt information, and charging selection information, and plan the transport path information of the AGV transport robot according to the A* algorithm; The AGV handling robot is used to obtain handling path information and complete the handling task accordingly; The central control module includes a parking space allocation unit, an information transmission unit and a route planning unit; The parking space allocation unit is used to determine whether the new energy charging parking lot can provide energy for the waiting vehicle according to the first allocation constraint condition. If not, no charging pile is allocated to the waiting vehicle. If yes, a charging pile is allocated to the waiting vehicle. The parking space is also allocated to the waiting vehicle after comprehensive analysis based on the energy driving mode and charging pile information of the waiting vehicle. The information transmission unit is used to obtain the energy driving mode and charging pile information of the vehicle to be stored from the garage data acquisition module, and send the transport path information to the AGV transport robot; The route planning unit is used to analyze the transport path information according to the parking spaces allocated to the vehicles to be stored and the AGV transport robot data; The first allocation constraint is: Wherein, F1 is the first allocation constraint, F1=0 means that energy cannot be replenished for the vehicles to be stored, F2 is the second allocation constraint, F1=F2 means that energy is replenished for the vehicles to be stored according to the second allocation constraint, DK is the number of idle charging piles, WK is the number of idle parking spaces, EN is the energy driving mode of the vehicles to be stored, EN=1 means that the energy driving mode of the vehicles to be stored is electric energy replenishment; The second allocation constraint is: Wherein, F2=1 means that energy can be replenished for the waiting vehicle, G1 is the charging pile available index, G2 is the parking space available index, F2=G1 means that energy is replenished for the waiting vehicle according to the charging pile available index, and F2=G2 means that energy is replenished for the waiting vehicle according to the parking space available index; When the charging pile availability index G1 is greater than a certain threshold, it indicates that energy can be replenished for the waiting vehicle, otherwise, energy cannot be replenished for the waiting vehicle; When the parking space availability index G2 is greater than a certain threshold, it indicates that energy can be replenished for the vehicles to be stored; otherwise, energy cannot be replenished for the vehicles to be stored.

2. The path planning system for a handling robot in a new energy charging parking lot according to claim 1, characterized in that: The garage data acquisition module includes a driving energy identification unit, a charging pile information acquisition unit and a garage data acquisition unit; The driving energy identification unit is used to obtain the vehicle identification information of the vehicle to be stored by the user, and obtain the energy driving mode of the vehicle to be stored according to the vehicle identification information; The charging pile information acquisition unit is used to acquire the charging pile information in the new energy charging parking lot, and the charging pile information includes the charging pile location information, the charging pile working status information, and the charging pile charging power; The garage data acquisition unit is used to acquire the garage data of the new energy charging parking lot, and the garage data includes parking room data, parking space data and AGV transport robot data.

3. The path planning system for a handling robot in a new energy charging parking lot according to claim 2, characterized in that: The garage data includes parking room data, parking space data and AGV handling robot data; The parking lot data includes parking lot location data and parking lot vacancy data; The parking space data includes parking space location data, parking space vacancy data, and charging pile location information; The AGV transport robot data includes real-time position data and real-time task status data.

4. The path planning system for a transport robot in a new energy charging parking lot according to claim 2, characterized in that: The information interaction module includes an energy replenishment time analysis unit, an information prompt visualization unit and a user selection acquisition unit; The energy replenishment time analysis unit is used to obtain an estimated charging amount according to the total energy amount of the user's vehicle to be stored, and to obtain an estimated charging time for the vehicle to be stored according to the charging power of the charging pile; The information prompt visualization unit is used to visualize the estimated charging time and estimated charging amount to the user; The user selection acquisition unit is used to acquire the total energy amount of the vehicle to be stored input by the user, and is also used to acquire the charging confirmation signal input by the user.

5. The path planning system for a handling robot in a new energy charging parking lot according to claim 1, characterized in that: The specific analysis method for allocating parking spaces for vehicles to be stored after comprehensive analysis is as follows: All charging piles in the new energy charging parking lot are movable charging piles, and the charging pile positions of the movable charging piles are randomly allocated in the new energy charging parking lot; After it is determined that a charging pile is to be allocated to the vehicle to be stored, the garage data in the new energy charging parking lot is obtained; Obtain information on all parked vehicles in the new energy charging parking lot and number all parked vehicles; Extract the number of available parking spaces based on the garage data, and extract the remaining waiting time for vehicles to be picked up based on the information of parked vehicles; When the number of parking spaces available is 0, stop accepting vehicles waiting to be stored whose energy driving mode is not electric energy replenishment mode; Construct a parking space availability index analysis formula, and analyze the parking space availability index based on it; The parking space availability indexes greater than a certain threshold are sorted from large to small, and the parking space corresponding to the maximum parking space availability index is allocated to the waiting vehicle for parking and waiting for energy replenishment; At the same time, the parked vehicles in the parking spaces corresponding to the maximum parking space availability index are moved to the parking room for temporary storage, and all other vehicles are stopped from being accepted.

6. The path planning system for a handling robot in a new energy charging parking lot as claimed in claim 5, characterized in that: The specific analysis method for allocating charging piles for vehicles to be stored is as follows: Obtaining the garage data in the new energy charging parking lot and the charging pile information of all movable charging piles, and numbering the movable charging piles; Obtain information on all parked vehicles in the new energy charging parking lot and number the parked vehicles; Extract the currently charged parked vehicle according to the parked vehicle information, and obtain the remaining charge amount corresponding to the currently charged parked vehicle and the remaining power of the current movable charging pile; Construct a charging pile availability index analysis formula, and analyze the charging pile availability index based on it; The charging piles with available indexes greater than a certain threshold are sorted from large to small, and the movable charging pile corresponding to the maximum value of the charging pile available index is allocated to the waiting vehicles for energy replenishment.

7. The path planning system for a transport robot in a new energy charging parking lot according to claim 6, characterized in that: The charging pile available index analysis formula is: Where ΔT1 is the maximum allowable waiting time for the charging pile to finish, EC k is the remaining charge capacity of the parked vehicle, k is the number of the currently charged parked vehicle, k = 1, 2, 3, ..., K, K is the total number of currently charged parked vehicles, W is the power of the charging pile, α1 is the weight of the waiting time of the charging pile in the charging pile availability index, ED k→i is the current remaining power of the mobile charging pile i corresponding to the currently charged parked vehicle k, i is the number of the mobile charging pile, i = 1, 2, 3, ..., I, I is the total number of mobile charging piles, when DK = 0, the number of mobile charging piles I is equal to the number of currently charged parked vehicles K, where i corresponds to k one by one, is the estimated charging capacity of the current waiting vehicle k0, and α2 is the weighted proportion of the remaining power that the mobile charging pile can provide for the waiting vehicle to replenish in the charging pile availability index.

8. The path planning system for a transport robot in a new energy charging parking lot as claimed in claim 5, characterized in that: The parking space availability index analysis formula is: G2=max[(ΔT2-T g )*β1+(N-SK-1)*β2], Where ΔT2 is the maximum allowed waiting time for the parking space to end, T g is the remaining waiting time for the parked vehicle, g is the number of all parked vehicles, g = 1, 2, 3, ..., G, G is the total number of all parked vehicles, β1 is the weighted proportion of the parking waiting time in the parking space availability index, N is the total number of parking rooms, SK is the remaining number of vacant parking rooms, and β2 is the weighted proportion of the remaining number of parking rooms in the parking space availability index.

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