Double-machine cooperative transfer robot system based on parameter optimization ratio and pairing method thereof

Abstract

The invention discloses a dual-machine cooperative transfer robot system based on parameter optimization matching and a pairing method thereof. The dual-machine cooperative transfer robot system comprises a plurality of transfer robots and a central control unit. An information acquisition module of the transfer robot acquires state information consisting of a loading force numerical range corresponding to the transfer robot, a distance numerical value between the cargos and gripping apparatus type information for gripping the cargos, and sends the state information to a central control unit; a matching function module of the central control unit obtains a cooperative adaptation value between the two transfer robots by optimizing a matching function, and a cooperative adaptation value number set is obtained through calculation of the multiple transfer robots in the no-load state according to the distribution mode that every two transfer robots are in one group; the instruction distribution module obtains a cooperative adaptive value number set, enables two carrying robots in the maximum value of the cooperative adaptive value number set to be paired, and controls the two carrying robots to carry goods cooperatively; the optimal two parties of collaborative operation of the transfer robot are selected, and the efficiency of controlling operation of the transfer robot is improved.

Description

Technical Field

[0001] The present invention relates to the field of robot control technology, and in particular to a dual-machine collaborative handling robot system based on parameter optimization ratio and a pairing method thereof. Background Art

[0002] In automated warehouses and production workshops, the collaborative operation of robots is a key factor in improving logistics efficiency and reducing labor costs. Currently, with the rapid development of industrial automation, the application of robotics in production and logistics is becoming more and more extensive. However, although robotics has brought many conveniences to the production process, the existing robot collaborative operation system still has some problems that need to be solved.

[0003] A significant problem in existing systems is the lack of an effective pairing mechanism. This means that the collaboration between robots is not always optimal, resulting in unreasonable resource allocation. For example, some robots may be idle due to a lack of effective task allocation, while others may be less efficient due to task overload. This unbalanced resource allocation not only affects the smoothness of the operation, but also reduces the overall efficiency of the operation.

[0004] In addition, due to the lack of intelligent coordination and optimization algorithms, existing systems often have difficulty achieving efficient coordination between robots when handling complex tasks. This is especially true when multiple robots are working at the same time, which may cause bottlenecks in the operation process and affect the progress of the entire production or logistics process.

[0005] In order to overcome these problems and improve the efficiency of robot collaborative work, more advanced pairing and coordination mechanisms need to be developed. Summary of the invention

[0006] In response to the above technical problems, the present invention provides a dual-machine collaborative handling robot system based on parameter optimization ratio and a pairing method thereof, which uses a matching function module and can reasonably assign different handling robots to the same cargo location according to the status information of the handling robot in an empty state, so as to jointly handle the cargo; thereby, the present invention optimizes the selection of the two handling robots for collaborative operation and improves the efficiency of controlling the operation of the handling robots.

[0007] In order to achieve the above technical objectives, the present invention adopts the following technical means:

[0008] A dual-machine collaborative handling robot system based on parameter optimization ratio, comprising a plurality of handling robots and a central control unit;

[0009] The handling robot includes a load-carrying module, a positioning module, a grasping module, an information collection module and a communication module;

[0010] The load-carrying module is used to carry goods, the positioning module is used to obtain the position of the transport robot, and the grabbing module is used to grab the goods; the information acquisition module obtains status information consisting of the load-carrying force value range corresponding to the transport robot, the distance value between the goods, and the type of gripper used to grab the goods; the communication module sends the status information to the central control unit;

[0011] The central control unit includes a receiving module, a matching function module and an instruction distribution module;

[0012] Among them, the receiving module receives the status information transmitted by the communication module and transmits it to the matching function module; the matching function module obtains the collaborative adaptation value between the two handling robots by optimizing the matching function, and calculates the collaborative adaptation value set for multiple handling robots in an empty state according to a two-by-two allocation method; the instruction allocation module obtains the collaborative adaptation value set, and pairs the two handling robots with the maximum value of the collaborative adaptation value set to control them to collaboratively handle the goods.

[0013] Preferably, the instruction distribution module includes:

[0014] A ratio unit, which is used to determine the maximum value of the data of the collaborative adaptation value set;

[0015] An instruction sending unit sends a pairing instruction to two of the handling robots with the maximum values ​​of the collaborative adaptation value set, so that the two handling robots move to the cargo together.

[0016] Preferably, the transport robot further comprises:

[0017] A gravity sensor is provided at the load module of the transport robot, and judges the load state of the transport robot according to the acquired gravity value; wherein the load state is divided into a loaded state and an empty state;

[0018] The communication module sends the corresponding load status to the central control unit.

[0019] A pairing method for a dual-machine collaborative handling robot system based on parameter optimization ratio, the method adopts the dual-machine collaborative handling robot system based on parameter optimization ratio; characterized in that the control method comprises the following steps:

[0020] S001: The central control unit obtains the location information of the goods to be transported, and sends the location information to the positioning modules of all transport robots. The positioning modules calculate the distance value between the goods and the positioning modules based on their own positions.

[0021] S002: The handling robot is in an empty state, and its information acquisition module obtains data of corresponding status information, and its communication module sends the data of the status information to the central control unit;

[0022] S003: The central control unit receives the status information and transmits it to the proportioning function module;

[0023] S004: The matching function module obtains the collaborative adaptation value between the two handling robots by optimizing the matching function, and calculates a set of collaborative adaptation values ​​for a plurality of handling robots in an empty state according to a method of allocating two by two.

[0024] S005: The instruction distribution module obtains a collaborative adaptation value set, and pairs two handling robots with the maximum value of the collaborative adaptation value set, and controls them to collaboratively handle the goods;

[0025] S006: The two handling robots that receive the command move together to the goods that need to be handled, and after the two grippers jointly fix the goods, the two load modules jointly carry the goods;

[0026] S007: The two transport robots that receive the command transport the goods to the target location together.

[0027] Preferably, the control method for determining the load state of the transport robot comprises the following steps:

[0028] S021: The gravity sensor obtains the real-time load force of the load module of the transport robot;

[0029] S022: judging the load state of the handling robot according to the acquired gravity value; listing the load state of the handling robot with a gravity value other than 0 as a loaded state, and listing the load state of the handling robot with a gravity value of 0 as an unloaded state;

[0030] S023: The transport robot in the empty state sends the state information data to the central control unit.

[0031] Preferably, the control method for controlling the movement of the transport robot comprises the following steps:

[0032] S051: The ratio unit determines the maximum value of the data of the collaborative adaptation value set;

[0033] S052: The instruction sending unit sends a pairing instruction to the two handling robots with the maximum values ​​of the collaborative adaptation value set;

[0034] S053: The communication module of the transport robot receives the instruction and moves to the cargo together.

[0035] Preferably, the formula of the optimized ratio function is as follows:

[0036] F(R i ,R j )=w1·f1(L i , L j )+w2·f2(D i ,D j )+w3·f3(C i ,C j )+w4·f4(S i ,S j );

[0037] Among them, F(R i , R j ) are two transport robots R i and R j The matching function value between them;

[0038] w1 is the weight coefficient of the load-carrying force scoring function, w2 is the weight coefficient of the distance scoring function, w3 is the weight coefficient of the gripper type scoring function, and w4 is the weight coefficient of the collaborative efficiency scoring function, which satisfies 1=w1+w2+w3+w4. The specific allocation ratio is determined according to the actual situation.

[0039] f1(L i ,L j ) is the load-carrying force scoring function, where f1(L i ,L j )=1÷|L i -L j |;L i and L j They are the optimal load-bearing capacity of the two handling robots;

[0040] f2(D i ,D j ) is the distance scoring function, where f2(D i ,D j )=1÷(D i -D j ) 2 ;D i and D j They are the distances from the two handling robots to the goods;

[0041] f3(C i ,C j ) is the distance scoring function, where C i and C j They are the types of grippers of the two handling robots;

[0042] f4(S i ,S j) is the distance scoring function, where f4(S i ,S j )=min(S i ,S j );S i and S j They are the collaborative efficiency scores of the two handling robots, which are obtained through past records.

[0043] The beneficial effects of the present invention are as follows:

[0044] First, the dual-machine collaborative handling robot system described in the present invention uses a matching function module, which can reasonably allocate different handling robots to the same cargo location according to the status information of the handling robots in the unloaded state, and jointly carry the cargo; thereby, the present invention selects the optimal two handling robots for collaborative operation, thereby improving the efficiency of controlling the operation of the handling robots.

[0045] Second, the dual-machine collaborative transport robot system described in the present invention is also provided with a gravity sensor connected to the load-carrying module to accurately judge the state of the transport robot; thereby, the present invention can timely update the loading status of all transport robots and reasonably allocate the transport robots used in the collaborative transport tasks.

[0046] Third, the pairing method described in the present invention calculates the collaborative adaptation value according to the load capacity, distance, gripper matching degree and collaborative efficiency of both parties by using an optimized matching function; thereby, by performing ratio judgment on all collaborative adaptation values, the best dual-machine collaborative robot can be effectively found, thereby improving the operating efficiency of the handling robot system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] The above and other aspects of the present invention will now be described, by way of example only, with reference to the accompanying drawings, in which: Figure 1 A schematic diagram of a dual-machine collaborative handling robot system of the present invention; Figure 2 A schematic diagram of a system of a handling robot according to the present invention; Figure 3 It is a schematic diagram of the flow of the dual-machine collaborative handling robot pairing method of the present invention.

[0052] In the figure: 100, central control unit; 210, receiving module; 220, matching function module; 230, instruction distribution module; 200, handling robot; 210, load-carrying module; 220, positioning module; 230, grasping module; 240, information collection module; 250, communication module. DETAILED DESCRIPTION

[0053] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0054] The present invention provides a dual-machine collaborative handling robot system based on parameter optimization ratio, comprising a plurality of handling robots and a central control unit;

[0055] The transport robot includes a load-bearing module, a positioning module, a gripping module, an information collection module and a communication module; wherein the load-bearing module is used to carry goods, the positioning module is used to obtain the position of the transport robot, and the gripping module is used to grip the goods; the information collection module obtains status information consisting of the load-bearing force value range corresponding to the transport robot, the distance value between the goods and the type of gripper used to grip the goods; the communication module sends the status information to the central control unit.

[0056] The central control unit includes a receiving module, a matching function module and an instruction distribution module; wherein the receiving module receives the status information transmitted by the communication module and transmits it to the matching function module; the matching function module obtains the collaborative adaptation value between the two handling robots by optimizing the matching function, and calculates a collaborative adaptation value set for multiple handling robots in an empty state according to a two-by-two allocation method; the instruction distribution module obtains the collaborative adaptation value set, and pairs the two handling robots with the maximum value of the collaborative adaptation value set to control them to collaboratively carry the goods.

[0057] The goods to be transported will be monitored in real time by the central control unit, which will select the best two transport robots from several unloaded transport robots to carry out collaborative transport of the goods. Then, the selection of the two transport robots for collaborative operation is optimized to improve the efficiency of controlling the operation of the transport robots.

[0058] Preferably, the instruction distribution module includes: a ratio unit, which is used to determine the maximum value of the data in the collaborative adaptation value set; and an instruction sending unit, which sends a pairing instruction to the two handling robots in the maximum value of the collaborative adaptation value set, so that they move to the cargo together. In this way, the present invention can clarify the instruction issuance process and improve the instruction sending speed.

[0059] Preferably, in order to know in real time which transport robots are in an unloaded state, the transport robot also includes: a gravity sensor, which is arranged at the load module of the transport robot, and judges the load state of the transport robot according to the acquired gravity value; wherein the load state is divided into a loaded state and an unloaded state; and the communication module sends the corresponding load state to the central control unit.

[0060] The dual-machine collaborative handling robot system of the present invention adopts a specially designed optimized pairing method to improve the pairing efficiency during collaboration, including the following steps:

[0061] S001: The central control unit obtains the location information of the goods to be transported, and sends the location information to the positioning modules of all transport robots. The positioning modules calculate the distance value between the goods and the positioning modules based on their own positions.

[0062] S002: The handling robot is in an empty state, and its information acquisition module obtains data of corresponding status information, and its communication module sends the data of the status information to the central control unit;

[0063] S003: The central control unit receives the status information and transmits it to the proportioning function module;

[0064] S004: The matching function module obtains the collaborative adaptation value between the two handling robots by optimizing the matching function, and calculates a set of collaborative adaptation values ​​for a plurality of handling robots in an empty state according to a method of allocating two by two.

[0065] S005: The instruction distribution module obtains a collaborative adaptation value set, and pairs two handling robots with the maximum value of the collaborative adaptation value set, and controls them to collaboratively handle the goods;

[0066] S006: The two handling robots that receive the command move together to the goods that need to be handled, and after the two grippers jointly fix the goods, the two load modules jointly carry the goods;

[0067] S007: The two transport robots that receive the command transport the goods to the target location together.

[0068] Preferably, in order to update the load status information of the transport robot in real time, the control method for determining the load status of the transport robot includes the following steps:

[0069] S021: The gravity sensor obtains the real-time load force of the load module of the transport robot;

[0070] S022: judging the load state of the handling robot according to the acquired gravity value; listing the load state of the handling robot with a gravity value other than 0 as a loaded state, and listing the load state of the handling robot with a gravity value of 0 as an unloaded state;

[0071] S023: The transport robot in the empty state sends the state information data to the central control unit.

[0072] Preferably, the control method for controlling the movement of the transport robot comprises the following steps:

[0073] S051: The ratio unit determines the maximum value of the data of the collaborative adaptation value set;

[0074] S052: The instruction sending unit sends a pairing instruction to the two handling robots with the maximum values ​​of the collaborative adaptation value set;

[0075] S053: The communication module of the transport robot receives the instruction and moves to the cargo together.

[0076] Preferably, the formula for optimizing the ratio function is as follows:

[0077] F(R i ,R j )=w1·f1(L i , L j )+w2·f2(D i ,D j )+w3·f3(C i ,C j )+w4·f4(S i ,S j );

[0078] Among them, F(R i , R j ) are two transport robots R i and R j The matching function value between them;

[0079] w1 is the weight coefficient of the load-bearing force scoring function, w2 is the weight coefficient of the distance scoring function, w3 is the weight coefficient of the gripper type scoring function, and w4 is the weight coefficient of the collaborative efficiency scoring function, which satisfies 1=w1+w2+w3+w4. The specific distribution ratio is determined based on actual conditions. Specifically, it can be allocated according to the distribution ratio of 1.5:2:4.5:2.

[0080] f1(L i ,L j ) is the load-carrying force scoring function, where f1(L i ,L j )=1÷|L i -Lj |;L i and L j They are the optimal load-bearing capacity of the two handling robots;

[0081] f2(D i ,D j ) is the distance scoring function, where f2(D i ,D j )=1÷(D i -D j ) 2 ;D i and D j They are the distances from the two handling robots to the goods;

[0082] f3(C i ,C j ) is the distance scoring function, where C i and C j They are the types of grippers of the two handling robots;

[0083] f4(S i ,S j ) is the distance scoring function, where f4(S i ,S j )=min(S i ,S j );S i and S j They are the collaborative efficiency scores of the two handling robots, which are obtained through past records. After each handling robot system is installed, a corresponding collaborative efficiency value table will be established in the central control unit. The collaborative efficiency values ​​therein will be set accordingly according to the efficiency of the corresponding handling robot system in collaborative operations.

Claims

1. A dual-machine collaborative handling robot system based on parameter optimization ratio, comprising a plurality of handling robots and a central control unit; characterized in that: The handling robot includes a load-carrying module, a positioning module, a grasping module, an information collection module and a communication module; The load-carrying module is used to carry goods, the positioning module is used to obtain the position of the transport robot, and the grabbing module is used to grab the goods; the information acquisition module obtains status information consisting of the load-carrying force value range corresponding to the transport robot, the distance value between the goods, and the type of gripper used to grab the goods; the communication module sends the status information to the central control unit; The central control unit includes a receiving module, a matching function module and an instruction distribution module; Among them, the receiving module receives the status information transmitted by the communication module and transmits it to the matching function module; the matching function module obtains the collaborative adaptation value between the two handling robots by optimizing the matching function, and calculates the collaborative adaptation value set for multiple handling robots in an empty state according to a two-by-two allocation method; the instruction allocation module obtains the collaborative adaptation value set, and pairs the two handling robots with the maximum value of the collaborative adaptation value set to control them to collaboratively handle the goods.

2. The dual-machine collaborative handling robot system based on parameter optimization ratio according to claim 1 is characterized in that: The instruction distribution module comprises: A ratio unit, which is used to determine the maximum value of the data of the collaborative adaptation value set; An instruction sending unit sends a pairing instruction to two of the handling robots with the maximum values ​​of the collaborative adaptation value set, so that the two handling robots move to the cargo together.

3. The dual-machine collaborative handling robot system based on parameter optimization ratio according to claim 1 is characterized in that: The handling robot also includes: A gravity sensor is provided at the load module of the transport robot, and judges the load state of the transport robot according to the acquired gravity value; wherein the load state is divided into a loaded state and an empty state; The communication module sends the corresponding load status to the central control unit.

4. A pairing method for a dual-machine collaborative handling robot system based on parameter optimization ratio, the method adopts the dual-machine collaborative handling robot system based on parameter optimization ratio as described in any one of claims 1 to 3; characterized in that: The control method comprises the following steps: S001: The central control unit obtains the location information of the goods to be transported, and sends the location information to the positioning modules of all transport robots. The positioning modules calculate the distance value between the goods and the positioning modules based on their own positions. S002: The handling robot is in an empty state, and its information acquisition module obtains data of corresponding status information, and its communication module sends the data of the status information to the central control unit; S003: The central control unit receives the status information and transmits it to the proportioning function module; S004: The matching function module obtains the collaborative adaptation value between the two handling robots by optimizing the matching function, and calculates a set of collaborative adaptation values ​​for a plurality of handling robots in an empty state according to a method of allocating two by two. S005: The instruction distribution module obtains a collaborative adaptation value set, and pairs two handling robots with the maximum value of the collaborative adaptation value set, and controls them to collaboratively handle the goods; S006: The two handling robots that receive the command move together to the goods that need to be handled, and after the two grippers jointly fix the goods, the two load modules jointly carry the goods; S007: The two transport robots that receive the command transport the goods to the target location together.

5. The pairing method of the dual-machine collaborative handling robot system based on parameter optimization ratio according to claim 4 is characterized in that: The control method for determining the load state of the handling robot comprises the following steps: S021: The gravity sensor obtains the real-time load force of the load module of the transport robot; S022: judging the load state of the handling robot according to the acquired gravity value; listing the load state of the handling robot with a gravity value other than 0 as a loaded state, and listing the load state of the handling robot with a gravity value of 0 as an unloaded state; S023: The transport robot in the empty state sends the state information data to the central control unit.

6. The pairing method of the dual-machine collaborative handling robot system based on parameter optimization ratio according to claim 4 is characterized in that: The control method for controlling the movement of the handling robot comprises the following steps: S051: The ratio unit determines the maximum value of the data of the collaborative adaptation value set; S052: The instruction sending unit sends a pairing instruction to the two handling robots with the maximum values ​​of the collaborative adaptation value set; S053: The communication module of the transport robot receives the instruction and moves to the cargo together.

7. The pairing method of a dual-machine collaborative handling robot system based on parameter optimization ratio according to claim 4 is characterized in that: The formula of the optimized ratio function is as follows: F(R i ,R j )=w1·f1(L i ,L j )+w2·f2(D i ,D j )+w3·f3(C i ,C j )+w4·f4(S i ,S j ); Among them, F(R i , R j ) are two transport robots R i and R j The matching function value between them; w1 is the weight coefficient of the load-carrying force scoring function, w2 is the weight coefficient of the distance scoring function, w3 is the weight coefficient of the gripper type scoring function, and w4 is the weight coefficient of the collaborative efficiency scoring function, which satisfies 1=w1+w2+w3+w4. The specific allocation ratio is determined according to the actual situation. f1(L i ,L j ) is the load-carrying force scoring function, where f1(L i ,L j )=1÷L i -L j ; L i and L j They are the optimal load-bearing capacity of the two handling robots; f2(D i ,D j ) is the distance score function, where f2(D i ,D j )=1÷(D i -D j ) 2 ;D i and D j They are the distances from the two handling robots to the goods; f3(C i ,C j ) is the distance scoring function, where C i and C j They are the types of grippers of the two handling robots; f4(S i ,S j ) is the distance scoring function, where f4(S i ,S j )=min(S i ,S j );S i and S j They are the collaborative efficiency scores of the two handling robots.

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