Multi-task parallel RGV transport vehicle cooperative control method

Abstract

The invention relates to the technical field of transport vehicles, in particular to a multi-task parallel RGV transport vehicle cooperative control method. Firstly, multi-sensor fusion information and transportation path information are acquired; then, an obstacle avoidance control value is obtained according to the multi-sensor fusion information, and obstacle avoidance control is carried out on the RGV in combination with obstacle position information; then, a rail switching control value is obtained according to the real-time position of the RGV, the current rail congestion degree and the rail switching node state, and rail switching control is conducted on the RGV through the rail switching control value; obtaining a path transportation control value of each sub-region in combination with the transportation path information and an average obstacle avoidance control value and an average rail switching control value in unit time; and finally, optimizing the vehicle path control of each sub-region by using a multi-target region path control optimization model, and obtaining a complete optimal path according to the optimal path of each sub-region.

Description

Technical Field

[0001] The present invention relates to the technical field of transport vehicles, and in particular to a multi-task parallel RGV transport vehicle collaborative control method. Background Art

[0002] Automation technology brings convenience to modern logistics and warehouse management, but it also brings disadvantages such as low transportation efficiency and unstable automated production. Therefore, RGV (Rail Guided Vehicle) was created. It can automatically connect with other logistics systems, reduce manual intervention, and enhance the flexibility of the transportation system.

[0003] With the continuous increase in transportation business, the current RGV transportation system still has shortcomings in the control and management of multi-task parallelism. The traditional RGV transportation control method uses hardware processing or software programming to control transportation. Although this can effectively control a single RGV transportation vehicle, it is impossible to achieve coordinated control between RGV transportation vehicles in the face of increasingly complex business and increasing transportation volume, which will reduce the efficiency and reliability of RGV transportation control.

[0004] Therefore, a multi-task parallel coordinated control method for RGV transport vehicles is proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a multi-task parallel RGV transport vehicle collaborative control method. First, obtain multi-sensor fusion information and transport path information; then, obtain the obstacle avoidance control value according to the multi-sensor fusion information, and perform obstacle avoidance control on the RGV transport vehicle in combination with the obstacle position information; then, obtain the track change control value according to the real-time position of the RGV transport vehicle, the current track congestion level and the track change node status, and use the track change control value to perform track change control on the RGV transport vehicle; combine the transport path information and the average obstacle avoidance control value and the average track change control value per unit time to obtain the path transport control value of each sub-area; finally, use the multi-objective area path control optimization model to optimize the vehicle path control of each sub-area, and obtain the complete optimal path based on the optimal path of each sub-area.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A multi-task parallel RGV transport vehicle cooperative control method, comprising:

[0008] Divide the working area into a plurality of sub-areas, each sub-area being provided with at least one track-changing node;

[0009] Acquire multi-sensor fusion information and transportation path information of the RGV transportation vehicles in each of the sub-areas;

[0010] Obtaining an obstacle avoidance control value of the RGV transport vehicle according to the multi-sensor fusion information, and performing obstacle avoidance control on the RGV transport vehicle in combination with the obstacle position information and the obstacle avoidance control value;

[0011] According to the real-time position of the RGV transport vehicle, the current track congestion level and the track change node status, the track change control value of the RGV transport vehicle is obtained, and the track change control of the RGV transport vehicle is performed using the track change control value;

[0012] Combining the transportation path information of each sub-area and the average obstacle avoidance control value and the average track change control value per unit time, obtaining a path transportation control value for each sub-area;

[0013] According to the path transport control value, regional transport time and regional business progress, the vehicle path control of each sub-area is optimized, and based on the optimal path of each sub-area, a complete optimal path connecting the operating area and the non-operating area is obtained.

[0014] Furthermore, the multi-sensor fusion information includes: ranging sensor information, pressure sensor information and visual sensor information; the ranging sensor, pressure sensor and visual sensor are respectively arranged on the front and rear sides, bottom and left and right sides of the RGV transport vehicle.

[0015] Furthermore, the transport path information includes: transport path location information and transport path frequency information; wherein, the transport path location information includes: regional transport starting point, regional track change node and regional transport end point.

[0016] Furthermore, according to the multi-sensor fusion information, an obstacle avoidance control value of the RGV transport vehicle is obtained, and the specific implementation process of performing obstacle avoidance control on the RGV transport vehicle in combination with the obstacle position information and the obstacle avoidance control value includes:

[0017] Obtaining the distance information collected by the distance measuring sensor, the load information collected by the pressure sensor, and the obstacle information collected by the visual sensor; wherein the obstacle information includes: obstacle quantity information and obstacle location information;

[0018] Compare the distance information and the load information with a distance threshold and a load threshold respectively to obtain a distance comparison value and a load comparison value;

[0019] Evaluate the distance comparison value, the load comparison value and the obstacle quantity information to obtain an obstacle avoidance control value;

[0020] According to the obstacle position information and the obstacle avoidance control value, the regional control unit determines whether to send an obstacle avoidance control command signal to the RGV transport vehicle.

[0021] Furthermore, according to the real-time position of the RGV transport vehicle, the current track congestion level and the state of the track change node, the track change control value of the RGV transport vehicle is obtained, and the specific implementation process of using the track change control value to control the track change of the RGV transport vehicle includes:

[0022] Obtain the real-time location and detention time of RGV transport vehicles on the current track, as well as the traffic volume and average vehicle speed;

[0023] Obtaining distance information between the RGV transport vehicle and the nearest track-changing node according to the real-time position;

[0024] Calculating the current track congestion level according to the detention time, the vehicle flow and the average vehicle speed;

[0025] Evaluate the distance information, the current track congestion level and the track change node status to obtain a track change control value;

[0026] According to the track-changing control value, the regional control unit determines whether to send a track-changing control instruction signal to the RGV transport vehicle.

[0027] Furthermore, according to the retention time, the vehicle flow and the average vehicle speed, the current track congestion degree is calculated as follows:

[0028]

[0029] Wherein, ydcd represents the current track congestion degree; zlsj represents the detention time; sm represents the number of vehicles per unit time; sm st It is represented as the standard value of traffic flow; sd is represented as the average speed of the vehicle per unit time; sd st It is expressed as the standard value of the average vehicle speed per unit time; λ1, λ2 and λ3 represent the vehicle detention time weight, vehicle quantity weight and vehicle speed weight respectively; exp() is expressed as an exponential function with a natural constant as the base.

[0030] Furthermore, the process of acquiring the track change node status includes:

[0031] Collect track monitoring data of each output branch of the track change node in the area;

[0032] Inputting the track monitoring data of each output branch into a track state recognition model for processing to obtain track transportation state information of each output branch;

[0033] The track transportation status information of each output branch is evaluated to obtain the track change node status.

[0034] Furthermore, the specific implementation process of obtaining the path transportation control value of each sub-area by combining the transportation path information of each sub-area and the average obstacle avoidance control value and the average track change control value per unit time includes:

[0035] Acquire the transportation path information of each of the sub-areas, and obtain the transportation path location information of each of the sub-areas according to the transportation path information;

[0036] Obtaining a transportation route for each of the sub-areas according to the transportation path location information;

[0037] According to the obstacle avoidance control value and the track change control value of the RGV transport vehicle in each transport route within a unit time, an average obstacle avoidance control value and an average track change control value are calculated;

[0038] The average obstacle avoidance control value and the average track change control value are evaluated to obtain the path transportation control value of each transportation route in each of the sub-areas.

[0039] Furthermore, according to the path transport control value, the regional transport time and the regional business progress, the vehicle path control of each sub-area is optimized, and according to the optimal path of each sub-area, a complete optimal path connecting the operation area and the non-operation area is obtained. The specific implementation process includes:

[0040] Obtain the path transportation control value, regional transportation time and regional business progress of the sub-region;

[0041] Construct a multi-objective regional path control optimization model, take the path transportation control value, the regional transportation time and the regional business progress as optimization objectives, and take the regional vehicle capacity and regional material capacity as constraints, optimize the vehicle path control of the sub-region, and obtain the optimal path for each of the sub-regions;

[0042] According to the optimal path of each sub-area, a complete optimal path connecting the working area and the non-working area is obtained.

[0043] Furthermore, it also includes: each sub-area is configured with an area control unit; the area control unit is used to calculate the obstacle avoidance control value, the track change control value and the path transportation control value, and at the same time send relevant control command signals to the RGV transport vehicle according to the obstacle avoidance control value, the track change control value and the path transportation control value.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] 1. The present invention proposes an obstacle avoidance control function for controlling the RGV transport vehicle to determine whether to avoid obstacles according to the actual situation. This function comprehensively evaluates the distance information collected by the distance measuring sensor, the load information collected by the pressure sensor, and the obstacle quantity information collected by the visual sensor, and uses the obstacle position information and the calculated obstacle avoidance control value to determine whether to issue an obstacle avoidance control instruction to the RGV transport vehicle; this function integrates the output data of multiple sensors to achieve effective obstacle avoidance control, further improving the efficiency and reliability of RGV transport control.

[0046] 2. The present invention proposes a track-changing control function for controlling the RGV transport vehicle to determine whether to change tracks according to actual conditions. This function first obtains the distance information between the RGV transport vehicle and the nearest track-changing node by using the real-time position of the vehicle; then, the current track congestion level is obtained according to the detention time, vehicle flow and average speed; then, the distance information, the current track congestion level and the state of the track-changing node are evaluated to obtain the track-changing control value; this function uses the track-changing control value to determine whether to send a track-changing control command signal to the RGV transport vehicle; this function uses the positional relationship between vehicles and the state of the track-changing node to achieve effective track-changing control, further improving the efficiency and reliability of RGV transport control.

[0047] 3. The present invention proposes a route control optimization function for optimizing the transport path control of each sub-region; the function constructs a multi-objective regional path control optimization model according to the path transport control value of the sub-region, the regional transport time, the regional business progress and other information; the function uses the multi-objective regional path control optimization model to obtain the optimal path of each sub-region, and obtains the complete optimal path based on the optimal path of each sub-region; the function combines the path transport control value, the regional transport information and the multi-objective optimization model to improve the efficiency and accuracy of the transport path control, and further improve the efficiency and reliability of the RGV transport control. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A schematic flow chart of a multi-task parallel RGV transport vehicle cooperative control method of the present invention;

[0049] Figure 2 A schematic diagram of a transport route in an operation area of ​​the present invention;

[0050] Figure 3 This is a schematic diagram of the second operation area transportation route of the present invention;

[0051] Figure 4 It is a structural schematic diagram of the track state recognition model of the present invention;

[0052] Figure 5 It is a schematic diagram of the structure of the regional control unit of the present invention.

[0053] In the figure: 1. Regional control unit; 2. Track change node; 3. Initial vehicle position; 4. Vehicle transportation position of route one; 5. Vehicle transportation position of route two. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Automation technology brings convenience to modern logistics and warehouse management, but it also brings disadvantages such as low transportation efficiency and unstable automated production. Therefore, RGV (Rail Guided Vehicle) was created. It can automatically connect with other logistics systems, reduce manual intervention, and enhance the flexibility of the transportation system.

[0056] With the continuous increase in transportation business, the current RGV transportation system still has shortcomings in the control and management of multi-task parallelism. The traditional RGV transportation control method uses hardware processing or software programming to control transportation. Although this can effectively control a single RGV transportation vehicle, it is impossible to achieve coordinated control between RGV transportation vehicles in the face of increasingly complex business and increasing transportation volume, which will reduce the efficiency and reliability of RGV transportation control.

[0057] Embodiment 1

[0058] The specific implementation process in the embodiment of the present application will be implemented by a multi-task parallel RGV transport vehicle cooperative control method of the present invention, see Figure 1 The process of the method proposed in the present invention is described in the following; the multi-task parallel RGV transport vehicle collaborative control method comprises:

[0059] S10. Obtain multi-sensor fusion information and transportation path information of the RGV transport vehicle;

[0060] S20. Obstacle avoidance control value is calculated based on the multi-sensor fusion information, and obstacle avoidance control is performed on the RGV transport vehicle in combination with the obstacle position information;

[0061] S30. According to the real-time position of the RGV transport vehicle, the current track congestion level and the state of the track change node, a track change control value is obtained, and the track change control value is used to control the track change of the RGV transport vehicle;

[0062] S40. Combining the transport path information and the average obstacle avoidance control value and the average track change control value per unit time, obtain the path transport control value of each sub-area;

[0063] S50. Utilize a multi-objective regional path control optimization model to optimize the vehicle path control of each sub-region, and obtain a complete optimal path based on the optimal path of each sub-region.

[0064] Furthermore, the specific implementation process of a multi-task parallel RGV transport vehicle cooperative control method is as follows:

[0065] Divide the working area into a plurality of sub-areas, each sub-area being provided with at least one track-changing node;

[0066] Acquire multi-sensor fusion information and transportation path information of the RGV transportation vehicles in each of the sub-areas;

[0067] Obtaining an obstacle avoidance control value of the RGV transport vehicle according to the multi-sensor fusion information, and performing obstacle avoidance control on the RGV transport vehicle in combination with the obstacle position information and the obstacle avoidance control value;

[0068] According to the real-time position of the RGV transport vehicle, the current track congestion level and the track change node status, the track change control value of the RGV transport vehicle is obtained, and the track change control of the RGV transport vehicle is performed using the track change control value;

[0069] Combining the transportation path information of each sub-area and the average obstacle avoidance control value and the average track change control value per unit time, obtaining a path transportation control value for each sub-area;

[0070] According to the path transport control value, regional transport time and regional business progress, the vehicle path control of each sub-area is optimized, and based on the optimal path of each sub-area, a complete optimal path connecting the operating area and the non-operating area is obtained.

[0071] In this embodiment, a multi-task parallel RGV transport vehicle collaborative control method is proposed. First, multi-sensor fusion information and transport path information are obtained; then, obstacle avoidance control values ​​are obtained based on the multi-sensor fusion information, and obstacle avoidance control is performed on the RGV transport vehicle in combination with the obstacle position information; then, track change control values ​​are obtained based on the real-time position of the RGV transport vehicle, the current track congestion level, and the track change node status, and the track change control values ​​are used to perform track change control on the RGV transport vehicle; the path transport control value of each sub-area is obtained by combining the transport path information and the average obstacle avoidance control value and the average track change control value per unit time; finally, the vehicle path control of each sub-area is optimized using a multi-objective area path control optimization model, and a complete optimal path is obtained based on the optimal path of each sub-area; this method can effectively improve the efficiency and reliability of RGV transport control.

[0072] For specific explanation, the present invention is described in conjunction with the following embodiments, as follows:

[0073] Divide the operation area into a plurality of sub-areas, each of which is provided with at least one track-changing node 2;

[0074] In this embodiment, the operation area is divided into 4 sub-areas. The transportation routes of the operation area can be referred to Figure 2 and Figure 3 , including: an area control unit 1, a track change node 2, an initial vehicle position 3, a route one vehicle transport position 4 and a route two vehicle transport position 5; the area control unit 1 is used to control the transport vehicles in the area; the track change node 2 is used to change the track; Figure 2 It can be seen that the RGV transport vehicle starts from the initial vehicle position 3, passes through the nearest track change node 2, and then moves upward to reach the route one vehicle transport position 4; or Figure 5 As shown, the RGV transport vehicle starts from the initial vehicle position 3, passes the nearest track change node 2, and then moves to the right to arrive at the vehicle transport position 5 of route two.

[0075] Furthermore, multi-sensor fusion information and transportation path information of the RGV transportation vehicles in each of the sub-areas are obtained.

[0076] Furthermore, the multi-sensor fusion information includes: ranging sensor information, pressure sensor information and visual sensor information; the ranging sensor, pressure sensor and visual sensor are respectively arranged on the front and rear sides, bottom and left and right sides of the RGV transport vehicle.

[0077] In this embodiment, the distance measuring sensor is used to obtain the distance value between the current RGV transport vehicle and the vehicles in front and behind; the pressure sensor is used to obtain the weight value of the material on the RGV transport vehicle, and the current load condition of the vehicle is judged according to the weight value; the visual sensor is used to obtain the obstacle information around the current RGV transport vehicle; the multi-sensor fusion solution can effectively improve the efficiency and reliability of RGV transport control.

[0078] Furthermore, the transport path information includes: transport path location information and transport path frequency information; wherein, the transport path location information includes: regional transport starting point, regional track change node and regional transport end point.

[0079] In this embodiment, the transportation path information is mainly used to calculate the path transportation control value of the RGV vehicle; the transportation path information can be obtained through GPS, RFID tags, indoor positioning systems and image processing; this information contains accurate location information and the number of times the path is passed, which provides a detailed data basis for the subsequent calculation of the path transportation control value, thereby effectively improving the efficiency and reliability of RGV transportation control.

[0080] Furthermore, according to the multi-sensor fusion information, an obstacle avoidance control value of the RGV transport vehicle is obtained, and the specific implementation process of performing obstacle avoidance control on the RGV transport vehicle in combination with the obstacle position information and the obstacle avoidance control value includes:

[0081] Obtaining the distance information collected by the distance measuring sensor, the load information collected by the pressure sensor, and the obstacle information collected by the visual sensor; wherein the obstacle information includes: obstacle quantity information and obstacle location information;

[0082] Further, the distance information and the load information are compared with a distance threshold and a load threshold respectively to obtain a distance comparison value and a load comparison value;

[0083] Furthermore, the distance comparison value, the load comparison value and the obstacle quantity information are evaluated to obtain an obstacle avoidance control value; wherein the calculation formula of the obstacle avoidance control value is:

[0084]

[0085] α1+α2+α3=1.0;

[0086] Wherein, BZKZ represents the obstacle avoidance control value; M represents the number of times data is recorded; α1 represents the spacing control coefficient; jl th It is represented as the spacing threshold; k represents the spacing information of the kth data; α2 represents the load control coefficient; fh thExpressed as the load threshold; fh k It is represented as the load information of the kth data; α3 is represented as the obstacle quantity control coefficient; zws k Represented as the obstacle quantity information of the kth data; zws th Expressed as the obstacle quantity threshold.

[0087] In this embodiment, the distance threshold, load threshold and obstacle quantity threshold are flexibly set by relevant personnel in this field according to actual conditions.

[0088] In this embodiment, the spacing control coefficient, the load control coefficient and the obstacle quantity control coefficient are set to 0.3, 0.3 and 0.4 respectively. Of course, the setting of the control coefficients can be flexibly adjusted according to actual needs.

[0089] Further, according to the obstacle position information and the obstacle avoidance control value, the regional control unit determines whether to send an obstacle avoidance control instruction signal to the RGV transport vehicle 3 .

[0090] In this embodiment, an obstacle avoidance control function is proposed to control the RGV transport vehicle to determine whether to avoid obstacles according to the actual situation. This function comprehensively evaluates the distance information collected by the distance measuring sensor, the load information collected by the pressure sensor, and the obstacle quantity information collected by the visual sensor, and uses the obstacle position information and the calculated obstacle avoidance control value to determine whether to issue an obstacle avoidance control instruction to the RGV transport vehicle; this function integrates the output data of multiple sensors to achieve effective obstacle avoidance control, further improving the efficiency and reliability of RGV transport control.

[0091] Furthermore, according to the real-time position of the RGV transport vehicle, the current track congestion level and the state of the track change node, the track change control value of the RGV transport vehicle is obtained, and the specific implementation process of using the track change control value to control the track change of the RGV transport vehicle includes:

[0092] Obtain the real-time location and detention time of RGV transport vehicles on the current track, as well as the traffic volume and average vehicle speed;

[0093] Further, the distance information between the RGV transport vehicle and the nearest track change node 2 is obtained according to the real-time position;

[0094] Furthermore, the current track congestion degree is calculated according to the retention time, the vehicle flow and the average vehicle speed; wherein the calculation formula of the current track congestion degree is:

[0095]

[0096] Wherein, ydcd represents the current track congestion degree; zlsj represents the detention time; sm represents the number of vehicles per unit time; sm st It is represented as the standard value of traffic flow; sd is represented as the average speed of the vehicle per unit time; sd st It is expressed as the standard value of the average vehicle speed per unit time; λ1, λ2 and λ3 represent the vehicle detention time weight, vehicle quantity weight and vehicle speed weight respectively; exp() is expressed as an exponential function with a natural constant as the base.

[0097] In this embodiment, the current track congestion level is used to determine the transportation congestion level of the current track; the smaller the value, the more congested the current transportation track is; the current track congestion level is calculated by comprehensively evaluating the detention time, the number of vehicles per unit time, and the average speed of the vehicles. This value can accurately reflect the transportation congestion status of the current track, thereby effectively helping to control RGV vehicle transportation.

[0098] Furthermore, the distance information, the current track congestion level and the track change node state are evaluated to obtain a track change control value; wherein the calculation formula of the track change control value is:

[0099]

[0100] β1+β2+β3=1.0;

[0101] Wherein, HGKZ represents the track change control value; N represents the number of times the data is recorded; β1 represents the distance weight factor; jdjl th Represented as the distance threshold between the vehicle and the node; jdjl i It is represented as the distance information between the vehicle and the node of the i-th data; β2 is represented as the weight factor of the current track congestion degree; ydcd th Represents the current track congestion threshold; ydcd i It is represented by the current track congestion degree of the i-th data; β3 is represented by the track change node state weight factor; jdzt i Represented as the track change node state of the i-th data.

[0102] In this embodiment, the distance threshold between the vehicle and the node and the current track congestion threshold are set by relevant personnel in this field according to actual conditions.

[0103] In this embodiment, the distance weight factor, the current track congestion weight factor and the track change node status weight factor are set to 0.35, 0.3 and 0.35 respectively. Of course, the setting of the control coefficient can be flexibly adjusted according to actual needs.

[0104] Further, according to the track-changing control value, the regional control unit determines whether to send a track-changing control instruction signal to the RGV transport vehicle.

[0105] In this embodiment, a track change control function is proposed to control the RGV transport vehicle to determine whether to change tracks according to the actual situation. This function first obtains the distance information between the RGV transport vehicle and the nearest track change node by using the real-time position of the vehicle; then, according to the detention time, vehicle flow and average speed, the current track congestion degree is obtained; then, the distance information, the current track congestion degree and the state of the track change node are evaluated to obtain the track change control value; this function uses the track change control value to determine whether to send a track change control command signal to the RGV transport vehicle; this function uses the position relationship between vehicles and the state of the track change node to achieve effective track change control, further improving the efficiency and reliability of RGV transport control.

[0106] Furthermore, the process of acquiring the track change node status includes:

[0107] Collect track monitoring data of each output branch of track change node 2 in the area;

[0108] Inputting the track monitoring data of each output branch into a track state recognition model for processing to obtain track transportation state information of each output branch;

[0109] The track transportation status information of each output branch is evaluated to obtain the track change node status.

[0110] The structure of the track state recognition model can be referred to Figure 4 , its main implementation process includes:

[0111] Acquire monitoring image data of the track;

[0112] Further, the monitoring image data is input into the input layer of the track state recognition model to obtain input features;

[0113] Further, the input features are input into a track feature extraction layer to obtain track features;

[0114] Further, the track mark layer of the recognition model is used to obtain the anchor frame of the image feature;

[0115] In this embodiment, the number of anchor frames is 5; the number of anchor frames can be flexibly adjusted according to the actual requirements of model accuracy and model calculation overhead.

[0116] Further, the features in the anchor frame are input into the track recognition layer to obtain the target recognition result;

[0117] Furthermore, the target recognition result is input into the output layer to obtain the track transportation status information.

[0118] In this embodiment, the track-changing node status is used to determine whether to control the RGV transport vehicle to perform a track-changing operation; the track-changing node status is acquired by using image recognition, mainly by using a track status recognition model to perform feature recognition and processing on monitoring image data; finally, the track-changing node status is obtained by evaluating the transport status information of each track; the use of the track-changing node status can effectively improve the efficiency and reliability of RGV transport control.

[0119] Furthermore, the specific implementation process of obtaining the path transportation control value of each sub-area by combining the transportation path information of each sub-area and the average obstacle avoidance control value and the average track change control value per unit time includes:

[0120] Acquire the transportation path information of each of the sub-areas, and obtain the transportation path location information of each of the sub-areas according to the transportation path information;

[0121] Obtaining a transportation route for each of the sub-areas according to the transportation path location information;

[0122] According to the obstacle avoidance control value and the track change control value of the RGV transport vehicle in each transport route within a unit time, an average obstacle avoidance control value and an average track change control value are calculated;

[0123] The average obstacle avoidance control value and the average track change control value are evaluated to obtain the path transportation control value of each of the transportation routes in each of the sub-areas; wherein the calculation formula of the path transportation control value is:

[0124]

[0125] Wherein, LGKZ represents the path transportation control value; ω represents the path transportation control coefficient, which is set to 0.5; Expressed as the average obstacle avoidance control value; It is represented by the average track change control value; P is represented by the number of RGV transport vehicles per unit time; BZKZ i It is represented as the obstacle avoidance control value of the i-th vehicle; HGKZ i It is represented as the track change control value of the i-th vehicle.

[0126] In this embodiment, a path transportation control value is proposed for optimizing the control of the overall transportation path; first, the transportation route is obtained; then, the path transportation control value is calculated according to the average obstacle avoidance control value and the average track change control value of the transportation route; the path transportation control value can accurately reflect the real-time status of each transportation path, thereby effectively improving the efficiency and reliability of RGV transportation control.

[0127] Furthermore, according to the path transport control value, the regional transport time and the regional business progress, the vehicle path control of each sub-area is optimized, and according to the optimal path of each sub-area, a complete optimal path connecting the operation area and the non-operation area is obtained. The specific implementation process includes:

[0128] Obtain the path transportation control value, regional transportation time and regional business progress of the sub-region;

[0129] Construct a multi-objective regional path control optimization model, take the path transportation control value, the regional transportation time and the regional business progress as optimization objectives, and take the regional vehicle capacity and regional material capacity as constraints, optimize the vehicle path control of the sub-region, and obtain the optimal path for each of the sub-regions;

[0130] Among them, the objective function F(X) of the multi-objective regional path control optimization model is expressed as:

[0131]

[0132] Where min represents the minimization function; f1 represents the path transportation control function; Q represents the number of paths in the area; LJKZ j is the path transportation control value of the jth path; T is the number of vehicles on the jth path; BZKZ (j,i) HGKZ is the obstacle avoidance control value of vehicle i in the jth path; (j,i) represents the track change control value of vehicle i on the jth path; f2 represents the regional time service control function; K represents the number of vehicles in the region; SJ m represents the transportation time of the mth vehicle; YM m represents the business transportation volume of the mth vehicle; YW th Indicates the standard volume of business transportation in a region; K max Expressed as the maximum vehicle capacity of the area; Expressed as the total amount of materials carried by vehicles in the area; C max Expressed as the maximum material capacity of the area described.

[0133] According to the optimal path of each sub-area, a complete optimal path connecting the working area and the non-working area is obtained.

[0134] In this embodiment, a route control optimization function is proposed to optimize the transportation path control of each sub-region; this function constructs a multi-objective regional path control optimization model according to the path transportation control value of the sub-region, the regional transportation time, the regional business progress and other information; this function uses the multi-objective regional path control optimization model to obtain the optimal path of each sub-region, and obtains the complete optimal path according to the optimal path of each sub-region; this function combines the path transportation control value, the regional transportation information and the multi-objective optimization model to improve the efficiency and accuracy of the transportation path control, and further improve the efficiency and reliability of the RGV transportation control.

[0135] Furthermore, it also includes: each sub-area is configured with an area control unit 1; the area control unit 1 is used to calculate the obstacle avoidance control value, the track change control value and the path transportation control value, and at the same time send relevant control command signals to the RGV transport vehicle according to the obstacle avoidance control value, the track change control value and the path transportation control value.

[0136] The structure of the regional control unit in this embodiment is as follows Figure 5 As shown, it includes: a data receiving unit, an obstacle avoidance control unit, a track change control unit, a path transportation control unit and a data sending unit; the data receiving unit is used to receive sensor data, monitoring data and command data from a control center; the obstacle avoidance control unit, the track change control unit and the path transportation control unit respectively perform corresponding obstacle avoidance control, track change control and path transportation control operations according to the obstacle avoidance control value, the track change control value and the output result of the multi-objective regional path control optimization model; the data sending unit is used to send feedback information to the RGV transport vehicle and the control center; the use of the regional control unit can effectively improve the efficiency of RGV transport control.

[0137] Embodiment 2

[0138] The present invention proposes a multi-task parallel RGV transport vehicle collaborative control method. In order to further verify the effectiveness of the RGV transport vehicle collaborative control method, the present invention conducts two sets of efficiency and reliability tests on the traditional control method based on the combination of software and hardware and the control method of the present invention. The present invention selects two warehouses A and B to conduct efficiency and reliability tests on the RGV transport vehicle control method.

[0139] The present invention first divides the operation area of ​​warehouse A into 5 sub-areas, each sub-area is guaranteed to have at least one track-changing node, and a regional control unit is deployed for data transmission and processing; in order to facilitate the comparison between the traditional control method and the control method of the present invention, a corresponding standard value of transportation time and a standard value of transportation volume are set for each sub-area; whether the standard value of transportation time is exceeded is judged according to the actual transportation time, and the degree of regional business completion is calculated according to the actual transportation volume and the standard value of transportation volume; 4 days are randomly selected in a week, and test data are selected once in the morning, noon and evening every day, and comparison data for five weeks is continuously obtained, and the proportion of not exceeding the standard value of transportation time and the average degree of regional business completion are calculated by the average method.

[0140] The present invention uses a multi-task parallel RGV transport vehicle cooperative control method proposed in Example 1 to control the RGV transport vehicle, and compares the obtained proportion of exceeding the standard value of transportation time and the average regional business completion degree with the corresponding calculation results obtained by the traditional control method; Table 1 is the comparison result of the RGV transport vehicle cooperative control of warehouse A:

[0141] From the results in Table 1, it can be seen that the calculation results of the average regional business completion degree of the method of the present invention are all above 90%, and the business completion degree is better than the result of the traditional control method; at the same time, compared with the traditional method, the RGV transport vehicle cooperative control method proposed by the present invention consumes less regional transportation time, which can show that the present invention can effectively improve the efficiency and reliability of RGV transportation control;

[0142] Table 1 Comparison results of RGV transport vehicle collaborative control in warehouse A

[0143]

[0144] In order to further test the calculation results and effectiveness of this method, this embodiment also collects comparison data of another warehouse B. According to the same preprocessing method and division method, the difference is that the proportion of each sub-area that does not exceed the standard value of transportation time and the average regional business completion degree are no longer considered, but the transportation time proportion data and business completion degree of the complete transportation process are directly obtained; 4 groups of data are selected for testing, and the comparison results of the RGV transport vehicle collaborative control of warehouse B are shown in Table 2;

[0145] Table 2 Comparison results of coordinated control of RGV transport vehicles in warehouse B

[0146]

[0147]

[0148] It can be seen from the results in Table 2 that, although the calculation results of each divided area are not compared, from the perspective of the overall transportation process, the RGV transport vehicle collaborative control method proposed in the present invention is higher than the traditional control method in terms of transportation efficiency and business completion volume, which shows that the present invention can effectively improve the efficiency and reliability of RGV transportation control.

[0149] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-task parallel RGV transport vehicle cooperative control method, characterized in that: include: Dividing the operation area into a plurality of sub-areas, each sub-area being provided with at least one track-changing node; Acquire multi-sensor fusion information and transportation path information of the RGV transportation vehicles in each of the sub-areas; Obtaining an obstacle avoidance control value of the RGV transport vehicle according to the multi-sensor fusion information, and performing obstacle avoidance control on the RGV transport vehicle in combination with the obstacle position information and the obstacle avoidance control value; According to the real-time position of the RGV transport vehicle, the current track congestion level and the track change node status, the track change control value of the RGV transport vehicle is obtained, and the track change control of the RGV transport vehicle is performed using the track change control value; Combining the transportation path information of each sub-area and the average obstacle avoidance control value and the average track change control value per unit time, obtaining a path transportation control value for each sub-area; According to the path transport control value, regional transport time and regional business progress, the vehicle path control of each sub-area is optimized, and based on the optimal path of each sub-area, a complete optimal path connecting the operating area and the non-operating area is obtained.

2. A multi-task parallel RGV transport vehicle cooperative control method according to claim 1, characterized in that: The multi-sensor fusion information includes: ranging sensor information, pressure sensor information and visual sensor information; the ranging sensor, pressure sensor and visual sensor are respectively arranged on the front and rear sides, bottom and left and right sides of the RGV transport vehicle.

3. The multi-task parallel RGV transport vehicle cooperative control method according to claim 1 is characterized in that: The transport path information includes: transport path location information and transport path frequency information; wherein, the transport path location information includes: a regional transport starting point, a regional track change node and a regional transport end point.

4. The multi-task parallel RGV transport vehicle cooperative control method according to claim 1 is characterized in that: The specific implementation process of obtaining the obstacle avoidance control value of the RGV transport vehicle according to the multi-sensor fusion information and performing obstacle avoidance control on the RGV transport vehicle in combination with the obstacle position information and the obstacle avoidance control value includes: Obtaining the distance information collected by the distance measuring sensor, the load information collected by the pressure sensor, and the obstacle information collected by the visual sensor; wherein the obstacle information includes: obstacle quantity information and obstacle location information; Compare the distance information and the load information with a distance threshold and a load threshold respectively to obtain a distance comparison value and a load comparison value; Evaluate the distance comparison value, the load comparison value and the obstacle quantity information to obtain an obstacle avoidance control value; According to the obstacle position information and the obstacle avoidance control value, the regional control unit determines whether to send an obstacle avoidance control instruction signal to the RGV transport vehicle.

5. The multi-task parallel RGV transport vehicle cooperative control method according to claim 1 is characterized in that: According to the real-time position of the RGV transport vehicle, the current track congestion level and the state of the track change node, the track change control value of the RGV transport vehicle is obtained, and the specific implementation process of using the track change control value to control the track change of the RGV transport vehicle includes: Obtain the real-time location and detention time of RGV transport vehicles on the current track, as well as the vehicle flow and average vehicle speed; Obtaining distance information between the RGV transport vehicle and the nearest track-changing node according to the real-time position; Calculating the current track congestion level according to the detention time, the vehicle flow and the average vehicle speed; Evaluate the distance information, the current track congestion level and the track change node status to obtain a track change control value; According to the track-changing control value, the regional control unit determines whether to send a track-changing control instruction signal to the RGV transport vehicle.

6. A multi-task parallel RGV transport vehicle cooperative control method according to claim 5, characterized in that: According to the retention time, the vehicle flow and the average vehicle speed, the calculation formula for the current track congestion degree is calculated as follows: Wherein, ydcd represents the current track congestion degree; zlsj represents the detention time; sm represents the number of vehicles per unit time; sm st It is represented as the standard value of traffic flow; sd is represented as the average speed of the vehicle per unit time; sd st It is expressed as the standard value of the average vehicle speed per unit time; λ1, λ2 and λ3 represent the vehicle detention time weight, vehicle quantity weight and vehicle speed weight respectively; exp() is expressed as an exponential function with a natural constant as the base.

7. The multi-task parallel RGV transport vehicle cooperative control method according to claim 1 is characterized in that: The process of acquiring the track-changing node status includes: Collect track monitoring data of each output branch of the track change node in the area; Inputting the track monitoring data of each output branch into a track state recognition model for processing to obtain track transportation state information of each output branch; The track transportation status information of each output branch is evaluated to obtain the track change node status.

8. The multi-task parallel RGV transport vehicle cooperative control method according to claim 1 is characterized in that: The specific implementation process of obtaining the path transportation control value of each sub-area by combining the transportation path information of each sub-area and the average obstacle avoidance control value and the average track change control value per unit time includes: Acquire the transportation path information of each of the sub-areas, and obtain the transportation path location information of each of the sub-areas according to the transportation path information; Obtaining a transportation route for each of the sub-areas according to the transportation path location information; According to the obstacle avoidance control value and the track change control value of the RGV transport vehicle in each transport route within a unit time, an average obstacle avoidance control value and an average track change control value are calculated; The average obstacle avoidance control value and the average track change control value are evaluated to obtain the path transportation control value of each transportation route in each of the sub-areas.

9. The multi-task parallel RGV transport vehicle cooperative control method according to claim 1, characterized in that: The specific implementation process of optimizing the vehicle path control of each sub-area according to the path transportation control value, the regional transportation time and the regional business progress, and obtaining the complete optimal path connecting the operation area and the non-operation area according to the optimal path of each sub-area includes: Obtain the path transportation control value, regional transportation time and regional business progress of the sub-region; Construct a multi-objective regional path control optimization model, take the path transportation control value, the regional transportation time and the regional business progress as optimization objectives, take the regional vehicle capacity and the regional material capacity as constraints, optimize the vehicle path control of the sub-region, and obtain the optimal path for each sub-region; According to the optimal path of each sub-area, a complete optimal path connecting the working area and the non-working area is obtained.

10. The multi-task parallel RGV transport vehicle cooperative control method according to claim 1, characterized in that: Also includes: Each of the sub-regions is configured with a regional control unit; The regional control unit is used to calculate the obstacle avoidance control value, the track change control value and the path transportation control value, and send relevant control command signals to the RGV transport vehicle according to the obstacle avoidance control value, the track change control value and the path transportation control value.

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