An intelligent double-layer garage universal parking space allocation system based on handling robots

Abstract

The present invention relates to the field of artificial intelligence technology. The present invention discloses an intelligent double-layer garage universal parking space allocation system based on a handling robot, comprising: a vehicle access information acquisition module, a handling robot state recognition module, a parking space state recognition module, a vehicle access path planning module, a handling robot handling module, a vehicle handling state monitoring module, an abnormality detection emergency braking module and an allocation system intelligent management module. A path planning model is established based on the idle handling robot information transmitted by the handling robot state recognition module and the recognition result of the parking space state recognition module to plan the path for access vehicles and determine the optimal path. A handling risk model is established based on the handling process to monitor the handling state of the handling robot during the vehicle handling process, and emergency braking is triggered when an abnormal state is detected. The vehicle handling and parking space allocation can be automatically completed through the cooperation of the handling robot, thereby reducing manual intervention and improving the overall operation efficiency.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and more specifically to an intelligent double-layer garage universal parking space allocation system based on a handling robot. Background Art

[0002] With the acceleration of urbanization and the continuous increase in the number of cars, the problem of difficult parking in cities has increasingly become a bottleneck restricting urban development. Traditional parking methods have problems such as low space utilization, low management efficiency, and difficulty in parking, which can no longer meet the needs of modern cities. Driven by technologies such as the Internet of Things, big data, and artificial intelligence, automation and intelligent technologies have been widely used in the transportation field. These technologies have made it possible to realize intelligent parking systems. Through intelligent management, automated control, and data sharing, intelligent operation and efficient management of parking lots can be achieved.

[0003] As a new parking method, the intelligent double-layer garage has significant advantages. First, the double-layer design can significantly increase the parking space and improve land utilization. Second, the intelligent management system can realize the automatic allocation of parking spaces and the automatic storage and retrieval of vehicles, thereby improving parking efficiency. However, the traditional intelligent double-layer garage sampling lifting system mainly focuses on the vertical lifting function and lacks autonomous navigation and positioning capabilities. It takes longer time and higher driving skills to enter the garage. The driver needs to adapt to the automated operation process of the garage and follow the instructions to park. The functions are relatively simple. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides an intelligent double-layer garage universal parking space allocation system based on a handling robot to solve the problems existing in the above-mentioned background technology.

[0005] The present invention provides the following technical solutions: an intelligent double-layer garage universal parking space allocation system based on a handling robot, comprising: a vehicle access information acquisition module, a handling robot state recognition module, a parking space state recognition module, a vehicle access path planning module, a handling robot handling module, a vehicle handling state monitoring module, an abnormal emergency braking detection module and an allocation system intelligent management module;

[0006] The vehicle access information collection module includes an access information collection unit and a vehicle information collection unit. The access information collection unit is used to collect the access requirements of the vehicle. The vehicle information collection unit detects and identifies the vehicle information using an external sensor.

[0007] The transport robot state recognition module identifies the working state of the transport robot based on the access requirements of the vehicle collected by the access information collection unit, and transmits the idle transport robot information to the vehicle access path planning module;

[0008] The parking space status recognition module recognizes the status of the vacant parking space according to the parking demand based on the access demand of the vehicle collected by the access information collection unit, locates and recognizes the parking space according to the vehicle pickup demand, and transmits the recognition result to the vehicle access path planning module;

[0009] The vehicle access path planning module receives the idle handling robot information transmitted by the handling robot state recognition module and the recognition result of the parking space state recognition module, establishes a path planning model to perform path planning for access vehicles, and transmits the planning result to the handling robot handling module;

[0010] The transport module of the transport robot receives the planning result transmitted by the vehicle access path planning module, and transports the vehicle through the sliding gear according to the planned path;

[0011] The vehicle handling state monitoring module establishes a handling risk model to monitor the handling state of the vehicle during the handling robot's handling process, and transmits the abnormality detection result to the abnormality detection emergency braking module;

[0012] The abnormality detection emergency braking module receives the abnormality detection result transmitted by the vehicle handling state monitoring module and triggers emergency braking for the abnormal state;

[0013] The distribution system intelligent management module intelligently manages abnormal vehicles that trigger emergency braking in the abnormal emergency braking detection module.

[0014] Preferably, in the vehicle access information collection module, the access information collection unit receives the parking and retrieval requests issued by the user, uses the license plate number of each vehicle as the unique identifier of the vehicle, and records the model, color, size and access time of the vehicle;

[0015] The vehicle information acquisition unit uses external sensors to detect and identify vehicle information, and the vehicle information includes: the vehicle starting point position, the vehicle target point position, the length index of different paths, the smoothness index of different paths, the safety index of different paths, the position of the transport robot in the local rectangular coordinate system in different time periods, and the coordinate position of the transport robot in the global environment in different time periods.

[0016] Preferably, in the transport robot state identification module, the working state of the transport robot includes an idle state and a non-idle state, and the transport robot receives task instructions from the access information acquisition unit through the control system.

[0017] Preferably, in the parking space status recognition module, the specific content of identifying the free parking space status according to the parking demand is: using an image acquisition device to collect image data of the double-layer garage, pre-processing the collected data, extracting key features of the parking space through image processing technology, detecting the parking space status in real time, the parking space status includes an idle state and a non-idle state, and automatically allocating an idle parking space to the vehicle that sends the parking demand;

[0018] The specific content of locating and identifying the parking space according to the vehicle pick-up demand is: locating the parking space number according to the vehicle information recorded when the vehicle is parked in the parking space, and identifying the location of the vehicle.

[0019] Preferably, in the vehicle access path planning module, the idle handling robot information transmitted by the handling robot state recognition module and the recognition result of the parking space state recognition module are received, and the path planning model is established to perform path planning for access vehicles. The specific contents are as follows:

[0020] Step S01: When receiving a parking request, the starting point of the target vehicle is calibrated as A and the target point is B; when receiving a pick-up request, the starting point of the target vehicle is calibrated as A and the target point is B;

[0021] Step S02: Assume that there are i paths from the starting point A to the target point B, each path contains j nodes, and every two adjacent nodes constitute a path segment, where j = 1, 2, 3, ..., m, expressed as ;

[0022] Step S03: Calculate the length index of each path, the calculation formula is: ,in represents the total length of each path, Represents a path segment Length;

[0023] Step S04: Calculate the smoothness index of each path, the calculation formula is: ,in represents the smoothness index of each path, Represents a path segment and The angle between represents a constant, Indicates the number of path segments for each path;

[0024] Step S05: Calculate the safety index of each path, the calculation formula is: ,in represents the safety index of each path, represents a constant, Represents a path segment and the closest obstacle in the environment to the path segment the distance to the path segment;

[0025] Step S06: Calculate the comprehensive feasibility index of each path based on the length index, smoothness index and safety index of each path. The calculation formula is: ,in represents the comprehensive feasibility index of each path, Indicates the weight value of the length index. Indicates the weight value of the smoothing indicator, Indicates the weight value of the safety index;

[0026] Step S07: Based on the comprehensive feasibility index of each path , select the maximum value of the comprehensive feasibility index within the preset threshold range The corresponding path is the optimal path, and the planning result is transmitted to the handling module of the handling robot.

[0027] Preferably, in the vehicle handling state monitoring module, the specific contents of establishing a handling risk model to monitor the handling state of the vehicle handling process by the handling robot are as follows:

[0028] Step S01: Divide the process of the transport robot transporting the vehicle into t time periods, where t=1, 2, 3, ..., T;

[0029] Step S02: Detect the position of the transport robot in the local rectangular coordinate system in different time periods through sensors ;

[0030] Step S03: Transfer the position of the handling robot in the local rectangular coordinate system in different time periods to the global coordinate system to obtain the coordinates of the handling robot in the global environment in different time periods. ;

[0031] Step S04: Calculate the distance between two consecutive time periods of the transport robot according to the coordinates of the transport robot in the global environment in different time periods to determine whether a transport risk occurs.

[0032] Preferably, in step S03, the positions of the transport robot in the local rectangular coordinate system in different time periods are transferred to the global environment to obtain the coordinates of the transport robot in the global environment in different time periods. The specific contents are as follows:

[0033] Step S1: Calculate the horizontal coordinate of the handling robot in the global environment in different time periods. The calculation formula is: ,in Represents the horizontal coordinate of the handling robot in the global environment in different time periods, represents the coordinate transformation coefficient, It represents the angle between the moving direction of the handling robot in the current time period and the x-axis of the global coordinate system. Indicates the angle between the moving direction of the handling robot in the current time period and the moving direction in the first time period. represents the horizontal coordinate of the handling robot in the local rectangular coordinate system in different time periods, Indicates the offset distance of the handling robot coordinates in different time periods;

[0034] Step S2: Calculate the vertical coordinate of the transport robot in the global environment in different time periods. The calculation formula is: ,in Represents the horizontal coordinate of the handling robot in the global environment in different time periods;

[0035] Step S3: completing the conversion of the position of the handling robot from the local rectangular coordinate system to the global coordinate system in different time periods.

[0036] Preferably, in step S04, the distance between two consecutive time periods of the transport robot is calculated based on the coordinates of the transport robot in the global environment in different time periods, and the specific contents of judging whether a transport risk occurs are as follows:

[0037] Step S1: Calculate the coordinates of the transport robot in the global environment in different time periods. Calculate the distance between two consecutive time periods. The calculation formula is: , where M(t, t+1) represents the distance between two consecutive time periods of the handling robot;

[0038] Step S2: Compare the distance M(t, t+1) between the transport robot in two consecutive time periods with the preset threshold For comparison, if the distance M(t, t+1) between two consecutive time periods of the transport robot is greater than the preset threshold , then the handling robot is judged to be in an abnormal state during the process of handling the vehicle. If the distance M (t, t+1) between two consecutive time periods of the handling robot is less than or equal to the preset threshold , it is judged that the handling status of the handling robot during the process of handling the vehicle is normal.

[0039] Preferably, in the abnormality detection emergency braking module, the abnormality detection result transmitted by the vehicle handling state monitoring module is received, and the system generates an emergency braking instruction and sends it to the handling robot control system to trigger emergency braking for the abnormal state, and the system records the braking process and results.

[0040] Preferably, in the distribution system intelligent management module, a corresponding report is generated based on the braking process and results recorded by the system, and intelligent management is performed on abnormal vehicles that trigger emergency braking in the abnormal emergency braking detection module.

[0041] Technical effects and advantages of the present invention:

[0042] The present invention is provided with a vehicle access information acquisition module, a handling robot state recognition module, a parking space state recognition module, a vehicle access path planning module, a handling robot handling module, a vehicle handling state monitoring module, an abnormality detection emergency braking module and an allocation system intelligent management module. A path planning model is established through the idle handling robot information transmitted by the handling robot state recognition module and the recognition result of the parking space state recognition module to plan the path for the access vehicle and determine the optimal path. A handling risk model is established based on the handling process to monitor the handling state of the vehicle handling process of the handling robot, and emergency braking is triggered when an abnormal state is detected. The vehicle handling and parking space allocation can be automatically completed through the cooperation of the handling robot, thereby reducing manual intervention and improving the overall operation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flow chart of an intelligent double-layer garage universal parking space allocation system based on a handling robot. DETAILED DESCRIPTION

[0044] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are merely illustrative. The intelligent double-layer garage universal parking space allocation system based on a transport robot involved in the present invention is not limited to the various structures recorded in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0045] like Figure 1 As shown, the present invention provides an intelligent double-layer garage universal parking space allocation system based on a handling robot, comprising: a vehicle access information acquisition module, a handling robot state recognition module, a parking space state recognition module, a vehicle access path planning module, a handling robot handling module, a vehicle handling state monitoring module, an abnormal emergency braking detection module and an allocation system intelligent management module;

[0046] The vehicle access information collection module includes an access information collection unit and a vehicle information collection unit. The access information collection unit is used to collect the access requirements of the vehicle. The vehicle information collection unit detects and identifies the vehicle information using an external sensor.

[0047] The transport robot state recognition module identifies the working state of the transport robot based on the access requirements of the vehicle collected by the access information collection unit, and transmits the idle transport robot information to the vehicle access path planning module;

[0048] The parking space status recognition module recognizes the status of the vacant parking space according to the parking demand based on the access demand of the vehicle collected by the access information collection unit, locates and recognizes the parking space according to the vehicle pickup demand, and transmits the recognition result to the vehicle access path planning module;

[0049] The vehicle access path planning module receives the idle handling robot information transmitted by the handling robot state recognition module and the recognition result of the parking space state recognition module, establishes a path planning model to perform path planning for access vehicles, and transmits the planning result to the handling robot handling module;

[0050] The transport module of the transport robot receives the planning result transmitted by the vehicle access path planning module, and transports the vehicle through the sliding gear according to the planned path;

[0051] The vehicle handling state monitoring module establishes a handling risk model to monitor the handling state of the vehicle during the handling robot's handling process, and transmits the abnormality detection result to the abnormality detection emergency braking module;

[0052] The abnormality detection emergency braking module receives the abnormality detection result transmitted by the vehicle handling state monitoring module and triggers emergency braking for the abnormal state;

[0053] The distribution system intelligent management module intelligently manages abnormal vehicles that trigger emergency braking in the abnormal emergency braking detection module.

[0054] In this embodiment, it should be specifically explained that in the vehicle access information collection module, the access information collection unit receives the parking and retrieval requests issued by the user, uses the license plate number of each vehicle as the unique identifier of the vehicle, and records the model, color, size and access time of the vehicle;

[0055] The vehicle information acquisition unit uses external sensors to detect and identify vehicle information, and the vehicle information includes: the vehicle starting point position, the vehicle target point position, the length index of different paths, the smoothness index of different paths, the safety index of different paths, the position of the transport robot in the local rectangular coordinate system in different time periods, and the coordinate position of the transport robot in the global environment in different time periods.

[0056] In this embodiment, it should be specifically explained that in the handling robot state identification module, the working state of the handling robot includes an idle state and a non-idle state, and the handling robot receives the task instruction of the access information acquisition unit through the control system;

[0057] The transport robot includes an independent and unique number, and the robot in an idle state receives a transport task issued by the system to perform a transport operation.

[0058] In this embodiment, it should be specifically explained that, in the parking space status recognition module, the specific content of identifying the free parking space status according to the parking demand is: using an image acquisition device to collect image data of the double-layer garage, pre-processing the collected data, extracting key features of the parking space through image processing technology, detecting the parking space status in real time, the parking space status includes an idle state and a non-idle state, and automatically allocating an idle parking space to the vehicle that sends the parking demand;

[0059] The specific content of locating and identifying the parking space according to the vehicle pick-up demand is: locating the parking space number according to the vehicle information recorded when the vehicle is parked in the parking space, and identifying the location of the vehicle.

[0060] In this embodiment, it should be specifically explained that, in the vehicle access path planning module, the idle handling robot information transmitted by the handling robot state recognition module and the recognition result of the parking space state recognition module are received, and the path planning model is established to perform path planning for the access vehicle. The specific contents are as follows:

[0061] Step S01: When receiving a parking request, the starting point of the target vehicle is calibrated as A and the target point is B; when receiving a pick-up request, the starting point of the target vehicle is calibrated as A and the target point is B, and the system automatically assigns the idle handling robot closest to the starting point of the target vehicle to carry out the handling of the target vehicle;

[0062] Step S02: Assume that there are i paths from the starting point A to the target point B, each path contains j nodes, and every two adjacent nodes constitute a path segment, where j = 1, 2, 3, ..., m, expressed as ;

[0063] Step S03: Calculate the length index of each path, the calculation formula is: ,in represents the total length of each path, Represents a path segment Length;

[0064] Step S04: Calculate the smoothness index of each path, the calculation formula is: ,in represents the smoothness index of each path, Represents a path segment and The angle between represents a constant, Indicates the number of path segments for each path;

[0065] Step S05: Calculate the safety index of each path, the calculation formula is: ,in represents the safety index of each path, represents a constant, Represents a path segment and the closest obstacle in the environment to the path segment the distance to the path segment;

[0066] Step S06: Calculate the comprehensive feasibility index of each path based on the length index, smoothness index and safety index of each path. The calculation formula is: ,in represents the comprehensive feasibility index of each path, Indicates the weight value of the length index. Indicates the weight value of the smoothing indicator, Indicates the weight value of the safety index;

[0067] Step S07: Based on the comprehensive feasibility index of each path , select the maximum value of the comprehensive feasibility index within the preset threshold range The corresponding path is the optimal path, and the planning result is transmitted to the handling module of the handling robot.

[0068] In this embodiment, it should be specifically explained that, in the handling module of the handling robot, the planning result transmitted by the vehicle access path planning module is received, and the handling robot performs vehicle handling through the sliding gear according to the planned path.

[0069] In this embodiment, it should be specifically explained that in the vehicle transport state monitoring module, the specific contents of establishing a transport risk model to monitor the transport state of the transport robot during the vehicle transport process are as follows:

[0070] Step S01: Divide the process of the transport robot transporting the vehicle into t time periods, where t=1, 2, 3, ..., T;

[0071] Step S02: Detect the position of the transport robot in the local rectangular coordinate system in different time periods through sensors ;

[0072] Step S03: Transfer the position of the handling robot in the local rectangular coordinate system in different time periods to the global coordinate system to obtain the coordinates of the handling robot in the global environment in different time periods. ;

[0073] Step S04: Calculate the distance between two consecutive time periods of the transport robot according to the coordinates of the transport robot in the global environment in different time periods to determine whether a transport risk occurs.

[0074] In this embodiment, it should be specifically explained that in step S03, the positions of the transport robot in the local rectangular coordinate system in different time periods are transferred to the global environment to obtain the coordinates of the transport robot in the global environment in different time periods. The specific contents are as follows:

[0075] Step S1: Calculate the horizontal coordinate of the handling robot in the global environment in different time periods. The calculation formula is: ,in Represents the horizontal coordinate of the handling robot in the global environment in different time periods, represents the coordinate transformation coefficient, It represents the angle between the moving direction of the handling robot in the current time period and the x-axis of the global coordinate system. Indicates the angle between the moving direction of the handling robot in the current time period and the moving direction in the first time period. represents the horizontal coordinate of the handling robot in the local rectangular coordinate system in different time periods, Indicates the offset distance of the handling robot coordinates in different time periods;

[0076] Step S2: Calculate the vertical coordinate of the transport robot in the global environment in different time periods. The calculation formula is: ,in Represents the horizontal coordinate of the handling robot in the global environment in different time periods;

[0077] Step S3: Complete the conversion of the position of the handling robot in the local rectangular coordinate system to the global coordinate system in different time periods, and obtain the coordinates of the handling robot in the global environment in different time periods after the conversion. .

[0078] In this embodiment, it should be specifically explained that in step S04, the distance between two consecutive time periods of the transport robot is calculated based on the coordinates of the transport robot in the global environment in different time periods, and the specific contents of judging whether a transport risk occurs are as follows:

[0079] Step S1: Calculate the coordinates of the transport robot in the global environment in different time periods. Calculate the distance between two consecutive time periods. The calculation formula is: , where M(t, t+1) represents the distance between two consecutive time periods of the handling robot;

[0080] Step S2: Compare the distance M(t, t+1) between the transport robot in two consecutive time periods with the preset threshold For comparison, if the distance M(t, t+1) between two consecutive time periods of the transport robot is greater than the preset threshold , then the handling robot is judged to be in an abnormal state during the process of handling the vehicle. If the distance M (t, t+1) between two consecutive time periods of the handling robot is less than or equal to the preset threshold , it is judged that the handling status of the handling robot during the process of handling the vehicle is normal.

[0081] In this embodiment, it should be specifically explained that in the abnormality detection emergency braking module, the abnormality detection result transmitted by the vehicle handling status monitoring module is received, and the system generates an emergency braking command and sends it to the handling robot control system to trigger emergency braking for the abnormal state, and the system records the braking process and results.

[0082] In this embodiment, it should be specifically explained that in the intelligent management module of the distribution system, a corresponding report is generated based on the braking process and results recorded by the system, and intelligent management is performed on the abnormal vehicles that trigger emergency braking in the abnormal emergency braking detection module. First, the transport robot's transport vehicle route is adjusted so that the transport robot continues to work according to the planned route. If the adjustment is unsuccessful, the current position of the transport robot is used as the starting point to re-plan the path from the starting point to the target point.

[0083] In the present embodiment, it should be specifically explained that the difference between the present embodiment and the prior art lies mainly in that the present embodiment is provided with a vehicle access information acquisition module, a handling robot state recognition module, a parking space state recognition module, a vehicle access path planning module, a handling robot handling module, a vehicle handling state monitoring module, an abnormality detection emergency braking module and an allocation system intelligent management module. Through the idle handling robot information transmitted by the handling robot state recognition module and the recognition result of the parking space state recognition module, a path planning model is established to plan the path for the access vehicle and determine the optimal path. Based on the handling process, a handling risk model is established to monitor the handling state of the vehicle handling process of the handling robot, and emergency braking is triggered when an abnormal state is detected. With the cooperation of the handling robot, the vehicle handling and parking space allocation can be automatically completed, the path can be flexibly planned, manual intervention can be reduced, and the overall operational efficiency can be improved.

[0084] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0085] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An intelligent double-layer garage universal parking space allocation system based on a handling robot, characterized by: include: Vehicle access information collection module, handling robot status recognition module, parking space status recognition module, vehicle access path planning module, handling robot handling module, vehicle handling status monitoring module, abnormality detection emergency braking module and distribution system intelligent management module; The vehicle access information collection module includes an access information collection unit and a vehicle information collection unit. The access information collection unit is used to collect the access requirements of the vehicle. The vehicle information collection unit detects and identifies the vehicle information using an external sensor. The transport robot state recognition module identifies the working state of the transport robot based on the access requirements of the vehicle collected by the access information collection unit, and transmits the idle transport robot information to the vehicle access path planning module; The parking space status recognition module, based on the access requirements of the vehicle collected by the access information collection unit, recognizes the status of the vacant parking space according to the parking requirements, locates and recognizes the parking space according to the vehicle pickup requirements, and transmits the recognition result to the vehicle access path planning module; The vehicle access path planning module receives the idle handling robot information transmitted by the handling robot state recognition module and the recognition result of the parking space state recognition module, establishes a path planning model to plan the path for accessing the vehicle, and transmits the planning result to the handling robot handling module; In the vehicle access path planning module, the specific contents of establishing a path planning model to plan the path for accessing vehicles are as follows: Step S01: When receiving a parking request, the starting point of the target vehicle is calibrated as A and the target point is B; when receiving a pick-up request, the starting point of the target vehicle is calibrated as A and the target point is B; Step S02: Assume that there are i paths from the starting point A to the target point B, each path contains j nodes, and every two adjacent nodes constitute a path segment, where j = 1, 2, 3, ..., m, expressed as ; Step S03: Calculate the length index of each path, the calculation formula is: ,in represents the total length of each path, Represents a path segment Length; Step S04: Calculate the smoothness index of each path, the calculation formula is: ,in represents the smoothness index of each path, Represents a path segment and The angle between represents a constant, Indicates the number of path segments for each path; Step S05: Calculate the safety index of each path, the calculation formula is: ,in represents the safety index of each path, represents a constant, Represents a path segment and the closest obstacle in the environment to the path segment the distance to the path segment; Step S06: Calculate the comprehensive feasibility index of each path based on the length index, smoothness index and safety index of each path. The calculation formula is: ,in represents the comprehensive feasibility index of each path, Indicates the weight value of the length index. Indicates the weight value of the smoothing indicator, Indicates the weight value of the safety index; Step S07: Based on the comprehensive feasibility index of each path , select the maximum value of the comprehensive feasibility index within the preset threshold range The corresponding path is the optimal path, and the planning result is transmitted to the handling module of the handling robot; The transport module of the transport robot receives the planning result transmitted by the vehicle access path planning module, and transports the vehicle through the sliding gear according to the planned path; The vehicle handling state monitoring module establishes a handling risk model to monitor the handling state of the vehicle during the handling robot's handling process, and transmits the abnormality detection result to the abnormality detection emergency braking module; The abnormality detection emergency braking module receives the abnormality detection result transmitted by the vehicle handling state monitoring module and triggers emergency braking for the abnormal state; The distribution system intelligent management module intelligently manages abnormal vehicles that trigger emergency braking in the abnormal emergency braking detection module.

2. According to claim 1, the intelligent double-layer garage universal parking space allocation system based on the handling robot is characterized by: In the vehicle access information collection module, the access information collection unit receives the parking and retrieval requests from the user, uses the license plate number of each vehicle as the unique identifier of the vehicle, and records the model, color, size and access time of the vehicle; The vehicle information acquisition unit uses external sensors to detect and identify vehicle information, and the vehicle information includes: the vehicle starting point position, the vehicle target point position, the length index of different paths, the smoothness index of different paths, the safety index of different paths, the position of the transport robot in the local rectangular coordinate system in different time periods, and the coordinate position of the transport robot in the global environment in different time periods.

3. According to claim 1, the intelligent double-layer garage universal parking space allocation system based on the handling robot is characterized by: In the transport robot state recognition module, the working state of the transport robot includes an idle state and a non-idle state, and the transport robot receives task instructions from the access information acquisition unit through the control system.

4. According to claim 1, the intelligent double-layer garage universal parking space allocation system based on the handling robot is characterized by: In the parking space status recognition module, the specific contents of identifying the status of the free parking space according to the parking demand are as follows: using an image acquisition device to collect image data of the double-layer garage, pre-processing the collected data, extracting key features of the parking space through image processing technology, detecting the parking space status in real time, the parking space status includes the free state and the non-free state, and automatically allocating the free parking space to the vehicle that sends the parking demand; The specific content of locating and identifying the parking space according to the vehicle pick-up demand is: locating the parking space number according to the vehicle information recorded when the vehicle is parked in the parking space, and identifying the location of the vehicle.

5. According to claim 1, the intelligent double-layer garage universal parking space allocation system based on the handling robot is characterized by: In the vehicle handling state monitoring module, the specific contents of establishing a handling risk model to monitor the handling state of the handling robot during the vehicle handling process are as follows: Step S01: Divide the process of the transport robot transporting the vehicle into t time periods, where t=1, 2, 3, ..., T; Step S02: Detect the position of the transport robot in the local rectangular coordinate system in different time periods through sensors ; Step S03: Transfer the position of the handling robot in the local rectangular coordinate system in different time periods to the global coordinate system to obtain the coordinates of the handling robot in the global environment in different time periods. ; Step S04: Calculate the distance between two consecutive time periods of the transport robot according to the coordinates of the transport robot in the global environment in different time periods to determine whether a transport risk occurs.

6. The intelligent double-layer garage universal parking space allocation system based on a handling robot according to claim 5 is characterized by: In step S03, the positions of the transport robot in the local rectangular coordinate system in different time periods are transferred to the global environment to obtain the coordinates of the transport robot in the global environment in different time periods. The specific contents are as follows: Step S1: Calculate the horizontal coordinate of the handling robot in the global environment in different time periods. The calculation formula is: ,in Represents the horizontal coordinate of the handling robot in the global environment in different time periods, represents the coordinate transformation coefficient, It represents the angle between the moving direction of the handling robot in the current time period and the x-axis of the global coordinate system. Indicates the angle between the moving direction of the handling robot in the current time period and the moving direction in the first time period. represents the horizontal coordinate of the handling robot in the local rectangular coordinate system in different time periods, Indicates the offset distance of the handling robot coordinates in different time periods; Step S2: Calculate the vertical coordinate of the transport robot in the global environment in different time periods. The calculation formula is: ,in Represents the horizontal coordinate of the handling robot in the global environment in different time periods; Step S3: completing the conversion of the position of the handling robot from the local rectangular coordinate system to the global coordinate system in different time periods.

7. The intelligent double-layer garage universal parking space allocation system based on a handling robot according to claim 5 is characterized by: In step S04, the distance between two consecutive time periods of the transport robot is calculated based on the coordinates of the transport robot in the global environment in different time periods, and the specific contents of judging whether a transport risk occurs are as follows: Step S1: Calculate the coordinates of the transport robot in the global environment in different time periods. Calculate the distance between two consecutive time periods. The calculation formula is: , where M(t, t+1) represents the distance between two consecutive time periods of the handling robot; Step S2: Compare the distance M(t, t+1) between the transport robot in two consecutive time periods with the preset threshold For comparison, if the distance M(t, t+1) between two consecutive time periods of the transport robot is greater than the preset threshold , then the handling robot is judged to be in an abnormal state during the process of handling the vehicle. If the distance M (t, t+1) between two consecutive time periods of the handling robot is less than or equal to the preset threshold , it is judged that the transporting status of the transport robot during the process of transporting the vehicle is normal.

8. The intelligent double-layer garage universal parking space allocation system based on a handling robot according to claim 1 is characterized by: In the abnormality detection emergency braking module, the abnormality detection result transmitted by the vehicle handling state monitoring module is received, and the system generates an emergency braking instruction and sends it to the handling robot control system to trigger emergency braking for the abnormal state, and the system records the braking process and results.

9. The intelligent double-layer garage universal parking space allocation system based on a handling robot according to claim 1 is characterized by: In the distribution system intelligent management module, a corresponding report is generated based on the braking process and results recorded by the system, and intelligent management is performed on abnormal vehicles that trigger emergency braking in the abnormal emergency braking detection module.

Images