"Negotiation - Decision" Market Auction Solving Method for Multi - Robot Task Allocation

Abstract

The present invention discloses a "negotiation - decision - making" market auction solution method for multi - robot task allocation, belonging to the field of multi - robot task allocation, which includes initializing information; announcing task area information and corresponding costs, and waiting for bids; making bids for each task area respectively; taking the task area as a unit, determining the priority according to each bid; randomly selecting a task area, and the one with the highest priority wins the bid; randomly selecting another task area from the remaining task areas until all task areas are allocated; under the condition of meeting the transfer condition, transferring the won task area for negotiation, and the transfer condition depends on mutual benefit; until the transfer condition cannot be met, the negotiation ends, and the total bid after transfer for each task area is reported upward; comparing the total bids each time, retaining the least one among them, and the corresponding allocation method for each task area is the final allocation method. The present invention uses an improved auction solution method to allocate target tasks with low cost and high democracy.

Description

Technical Field

[0001] The present invention relates to the technical field of robot task allocation, and particularly to a "negotiation - decision - making" market auction solution method for multi - robot task allocation. Background Technique

[0002] The demand for robots to solve increasingly complex and diverse problems is growing, which determines that a single robot is no longer the best solution; at the same time, robot teams must coordinate intelligently to successfully execute tasks. Driven by these demands, many research efforts have focused on the challenges of multi - robot coordination, and the multi - robot task allocation problem is one of them.

[0003] In recent years, negotiation - based and market - based multi - robot coordination methods have been widely used. Simply put, it can be understood as an "auction". First, the auction robot publishes task information to other robots in the team and requests bids; then, each robot in the team prepares a bid for the task according to its own execution ability and then forwards the bid to the auction robot; finally, the auction robot allocates the task to the robot with the highest bid.

[0004] On this basis, a free - market - based coordination method can be envisioned. Different from traditional market methods, it allows robots to negotiate, that is, they can compete and cooperate again after the task allocation, benefit from each other, and achieve win - win cooperation to maximize the overall benefit. This is what is called "negotiation".

[0005] Based on the free - market, it is also possible to envision a "decision - maker" in the team. The decision - maker can understand the current state of the team through communication or some form of observation and finally decide the final plan. This is what is called "decision - making".

[0006] Therefore, there is an urgent need for an auction solution method that can allocate target tasks at low cost and with high democracy. Summary of the Invention

[0007] The purpose of the present invention is to provide a "negotiation - decision - making" market auction solution method for multi - robot task allocation to solve the problems existing in the above - mentioned prior art, and to allocate target tasks at low cost and with high democracy by using an improved auction solution method.

[0008] To achieve the above - mentioned purpose, the present invention provides the following solution: The present invention provides a "negotiation - decision - making" market auction solution method for multi - robot task allocation, which is realized through the following steps:

[0009] Step S1: Initialize information;

[0010] Step S2: Announce the task area information and the corresponding costs, and wait for bids;

[0011] Step S3: Quote for each task area separately;

[0012] Step S4: Determine the priority according to each quote with the task area as the unit;

[0013] Step S5: Randomly select a task area, and it is won by the highest priority;

[0014] Step S6: Randomly select another task area from the remaining task areas, and repeat the process in Step S5 until all task areas are assigned;

[0015] Step S7: Under the condition of achieving transfer, transfer the won task area for negotiation, and the transfer condition depends on mutual benefit;

[0016] Step S8: Repeat Step S7 until the transfer condition cannot be achieved, the negotiation ends, and the total quote after transfer for each task area is reported upward;

[0017] Step S9: Compare the total quotes each time, retain the least one of them, and the corresponding allocation method for each task area is the final allocation method.

[0018] Preferably, in Step S3, the quote is determined between 85% and 115% of the cost price.

[0019] Preferably, in Step S4, 85% to 100% of the cost price represents a lower willingness for this task area, so the priority is lower; 100% to 115% of the cost price represents a higher willingness for this task area, so the priority is higher; with the task area as the unit, the higher the quote, the higher the priority will be obtained.

[0020] Preferably, in Step S7, the transfer condition is that the selling price is between 85% and 100% of the auction price, and the purchase price should be higher than its initial quote for this task area.

[0021] A "negotiation - decision" market auction solution system for multi - robot task allocation, including: a decision - making unit, multiple cooperation units, multiple task area units, an initialization unit, a data transmission unit, a profit - loss calculation unit, a quote determination unit, a priority determination unit, a priority comparison unit, an allocation unit, a transfer negotiation unit, a transfer condition judgment unit, a total quote comparison unit;

[0022] The decision - making unit initializes the information of the cooperation unit and the information of the task area unit through the initialization unit;

[0023] The decision-making unit transmits the information of the task area unit and the corresponding cost to the cooperation unit through the data transmission unit, and waits for the cooperation unit to make an offer;

[0024] The cooperation unit calculates the profit and loss through the profit and loss calculation unit, and transmits the calculation result to the offer determination unit to determine the offer for each task area unit;

[0025] The offer determination unit transmits each offer information to the decision-making unit for collection, and the decision-making unit determines the priority of the offer of the cooperation unit for each task area unit through the priority determination unit;

[0026] The decision-making unit randomly selects a task area unit through the allocation unit, determines the cooperation unit with the highest offer priority for the task area unit through the priority comparison unit, and allocates the task area unit to the cooperation unit through the allocation unit;

[0027] The decision-making unit allocates all the task area units to the cooperation unit through the allocation unit;

[0028] Each cooperation unit sequentially provides the allocated task area unit to other cooperation units through the transfer negotiation unit, and uses the transfer condition judgment unit to determine whether the transfer negotiation unit makes a transfer;

[0029] The decision-making unit compares the total offers each time and retains the lowest one.

[0030] Preferably, the offer determination unit makes an offer between 85% and 115% of the cost price; 85% to 100% of the cost price means that the cooperation unit hopes to obtain the task area unit by offering a price lower than the cost, that is, the willingness to the task area unit is relatively low; 100% to 115% of the cost price means that the cooperation unit hopes to obtain the task area unit by offering a price higher than the cost, that is, the willingness to the task area unit is relatively high.

[0031] Preferably, the transfer condition determined by the transfer condition judgment unit is that the selling price is between 85% and 100% of the auction price, and the purchase price of the cooperation unit that finally purchases the task area unit should be higher than the offer of the cooperation unit for the task area unit in the initial auction.

[0032] Preferably, the total offer information stored in the transfer negotiation unit is transmitted to the decision-making unit, and the decision-making unit compares the total offers each time through the total offer comparison unit.

[0033] The present invention discloses the following technical effects: By using the present method, the robots in the team can negotiate autonomously, transfer the initially assigned tasks, and the auction robot can compare the total costs after each negotiated transfer, and finally select the solution with the lowest cost. Such a task allocation method is easy to implement and has a good effect on reducing the total cost of the team. The present invention adopts an improved auction solving method to achieve low-cost and high-democracy allocation of target tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0035] Figure 1 It is a flowchart of the "negotiation-decision" market auction solving method for multi-robot task allocation in the embodiment;

[0036] Figure 2 It is a schematic diagram of the application scenario in the embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0038] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0039] The present invention provides a "negotiation-decision" market auction solving method for multi-robot task allocation, which can be applied to various application scenarios and is realized through the following steps:

[0040] Step S1: Initialize the information of the team robots and the task areas;

[0041] Step S2: The auction robot makes a decision, announces the task area information and the corresponding costs to the team robots, and waits for bids;

[0042] Step S3: The team robots bid for each task area respectively;

[0043] Step S4: Taking the task area as a unit, the auction robot determines the priority according to each bid;

[0044] Step S5: The auction robot randomly selects a task area, and it is won by the team robot with the highest priority.

[0045] Step S6: The auction robot randomly selects another task area from the remaining task areas and repeats the process in Step S5 until all task areas are assigned.

[0046] Step S7: Under the condition of transfer being achieved, the won task area is transferred for negotiation, and the transfer condition depends on mutual benefit.

[0047] Step S8: Repeat Step S7 until the transfer condition cannot be achieved, then the negotiation ends, and the total offer price after transfer for each task area is reported to the auction robot.

[0048] Step S9: The auction robot compares the total offer prices each time and retains the lowest one. The corresponding task area allocation method is the final allocation method.

[0049] For a further optimized solution, in Step S3, the offer price is determined between 85% and 115% of the cost price.

[0050] For a further optimized solution, in Step S4, 85% to 100% of the cost price represents a lower willingness to the task area, so the priority is lower; 100% to 115% of the cost price represents a higher willingness to the task area, so the priority is higher; taking the task area as a unit, the higher the offer price, the higher the priority will be obtained.

[0051] For a further optimized solution, in Step S7, the transfer condition is that the selling price is between 85% and 100% of the auction price, and the purchase price of the robot that finally purchases the task area should be higher than the offer price of the robot for this area in the initial auction.

[0052] Based on the above method, the present invention provides a "negotiation - decision" market auction solution system for multi - robot task allocation, including: a decision - making unit, multiple cooperation units, multiple task area units, an initialization unit, a data transmission unit, a profit - loss calculation unit, an offer price determination unit, a priority determination unit, a priority comparison unit, an allocation unit, a transfer negotiation unit, a transfer condition judgment unit, and a total offer price comparison unit.

[0053] The decision - making unit initializes the information of the cooperation unit and the information of the task area unit through the initialization unit.

[0054] The decision - making unit transmits the information of the task area unit and the corresponding cost to the cooperation unit through the data transmission unit and waits for the cooperation unit to make an offer.

[0055] The cooperation unit calculates the profit and loss through the profit and loss calculation unit, and transmits the calculation result to the determined quotation unit to determine the quotation for each task area unit;

[0056] The determined quotation unit transmits each quotation information to the decision-making unit for collection. The decision-making unit determines the priority of the cooperation unit's quotation for each task area unit through the priority determination unit;

[0057] The decision-making unit randomly selects a task area unit through the allocation unit, determines the cooperation unit with the highest priority for the quotation of the task area unit through the priority comparison unit, and allocates the task area unit to the cooperation unit through the allocation unit;

[0058] The decision-making unit allocates all task area units to the cooperation unit through the allocation unit;

[0059] Each cooperation unit sequentially provides the allocated task area unit to other cooperation units through the transfer negotiation unit, and uses the transfer condition judgment unit to determine whether the transfer negotiation unit makes a transfer;

[0060] The decision-making unit compares the total quotations each time and retains the least one. The corresponding allocation method for each task area is the final allocation method.

[0061] For a further optimized solution, the determined quotation unit quotes between 85% and 115% of the cost price; 85% to 100% of the cost price means that the cooperation unit hopes to obtain the task area unit by offering a price lower than the cost, that is, the willingness to the task area unit is relatively low; 100% to 115% of the cost price means that the cooperation unit hopes to obtain the task area unit by offering a price higher than the cost, that is, the willingness to the task area unit is relatively high.

[0062] For a further optimized solution, the transfer condition determined by the transfer condition judgment unit is that the selling price is between 85% and 100% of the auction price, and the purchase price of the cooperation unit that finally purchases the task area unit should be higher than the quotation of the cooperation unit for the task area unit in the initial auction.

[0063] For a further optimized solution, the total quotation information stored in the transfer negotiation unit is transmitted to the decision-making unit, and the decision-making unit compares the total quotations each time through the total quotation comparison unit.

[0064] Embodiment

[0065] Refer to Figure 1-2, this embodiment is described by taking the application in an industrial park as an example. As a typical large-scale production and logistics integration system under the collaboration of multiple enterprises / multiple units, in the case of customized requirements, due to the randomness of customer orders, the dynamics of production requirements, the serviceability of external resources, and the low repeatability of the production process, its operation process is inevitably affected by dynamic interferences from aspects such as orders, resources, and services. Therefore, the coordination of "production - transportation - warehousing" within the industrial park is extremely important. In such an industrial park with "production - transportation - warehousing" coordination, whether it is from the production area to the transfer area (transfer area / buffer area) (indoor / outdoor), or from the transfer area to the warehousing area (outdoor), the problem of task allocation is involved. If the vehicles passing through it are regarded as robots, then this is a multi-robot task allocation problem. In view of this, this embodiment provides a "negotiation - decision" market auction solution method for multi-robot task allocation, enabling the transport fleet to self-organize and allocate and execute the transport tasks within the industrial park.

[0066] Specifically, it is implemented through the following steps:

[0067] Step S1: The fleet decision-making robot (hereinafter referred to as DM) initializes the information of each member robot (i.e., member vehicle, hereinafter referred to as MR) and the transport task information;

[0068] The information of each MR includes: vehicle number, unit cost of vehicle driving;

[0069] Initialize the transport task information of each area, and the transport task information includes: area number, area distance.

[0070] In this embodiment, each information includes: MR number i, DM number i0, unit cost of vehicle driving c i , and the transport task information of each includes: area number j, area distance d.

[0071] In the initial state, DM knows the numbers, distances of all areas and the unit driving costs of each MR.

[0072] Step S2: DM announces to all MRs the areas of all transport tasks and their corresponding costs, and waits for the bids from MRs;

[0073] Step S3: MR comprehensively considers its own willingness to bid for all known tasks and determines the bid for each task between 85% and 115% of the cost price;

[0074] 85% to 100% of the cost price represents that this MR hopes to obtain this task by offering a price lower than the cost, that is, the willingness for this task is relatively low;

[0075] 100% to 115% of the cost price indicates that the MR hopes to obtain the task by offering a bid higher than the cost, that is, the willingness to this task is relatively high.

[0076] At this time, the range of the bid value bid of MRi for task area j is: 0.85*c i *d ≤ bid ij ≤ 1.15*c i *d.

[0077] Step S4: The DM collects all the bids of all MRs for all task areas, and determines the priority of the MRs who bid for this area in units of task areas;

[0078] Within each task area, the higher the bid of the MR, the higher the priority will be obtained;

[0079] Step S5: The DM randomly selects one from all task areas and matches the corresponding MR to complete this task;

[0080] The MR with the highest priority corresponding to this area will become the winner of this area and will obtain the right to complete the transportation of the task in this area;

[0081] Step S6: The DM randomly selects one from the remaining task areas again and repeats the process of Step S5;

[0082] Repeat Step S6 until all task areas have been assigned corresponding MRs by the DM;

[0083] Step S7: Each MR sequentially provides the area it won to other MRs for negotiation on task transfer;

[0084] Conditions for reaching a transferred task: For the vehicle selling the task, the selling price should be between 85% and 100% of the auction price. For the vehicle accepting this task, the purchase price should be higher than its initial bid for this area;

[0085] That is, a certain MR wins a certain task area at price A, and then sells this area to another MR at price C. The bid of this MR for this task area in the initial auction is B.

[0086] At this time, the relationship among prices A, B, and C should be: A > C > B (the relationship between A and C: 0.85A ≤ C ≤ A);

[0087] Step S8: Repeat Step S7 until no new and mutually beneficial transactions are possible and the negotiation ends;

[0088] During the entire negotiation process, the total quotes of all vehicles after each task transfer should be reported to the DM.

[0089] Step S9: The DM compares the total quotes each time and retains the lowest one. The corresponding task allocation plan for each region is the final task allocation plan. This method is applicable to the "negotiation - decision" market auction solution system for the above - mentioned multi - robot task allocation.

[0090] In this embodiment, on the basis of the traditional market auction method, the functions of member negotiation within the group and leadership decision - making are added. Each MR first reports its bids for each task to the DM based on its own situation. The DM sets priorities for these bids and allocates tasks to obtain an initial task allocation plan. Then, under the supervision of the DM, the MRs conduct internal negotiations to transfer tasks to each other. The DM saves the total cost after each negotiation of the MRs and selects the one with the lowest quote as the final allocation plan. The most significant advantage of the above - mentioned method provided in this embodiment is that the MRs in the fleet can negotiate autonomously to transfer the initially allocated tasks. At the same time, there is a decision - maker DM in the fleet who can compare the total cost after each negotiation and transfer, and finally select the plan with the lowest cost. Such a task allocation method is easy to implement and has a good effect on reducing the total cost of the team.

[0091] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0092] The above - described embodiments are only descriptions of the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A "negotiation - decision" market auction solution method for multi - robot task allocation, characterized in that Achieved through the following steps: Step S1: Initialize information; Step S2: Announce the task area information and corresponding costs, and wait for quotes; Step S3: Quote for each task area separately; Step S4: Determine the priority based on each quote for each task area; Step S5: Randomly select a task area, and the one with the highest priority wins the bid; Step S6: Randomly select another task area from the remaining task areas, and repeat the process in Step S5 until all task areas are allocated; Step S7: Under the condition of transfer being achieved, transfer the task area won in the bid for negotiation, and the transfer condition is based on mutual benefit; In Step S7, the transfer condition is that the selling price is between 85% and 100% of the bid price, and the purchase price should be higher than its initial quote for this task area; Step S9: Repeat Step S7 until the transfer condition cannot be achieved, the negotiation ends, and the total quote after transfer for each task area is reported upwards; Step S10: Compare the total quotes each time, retain the least one among them, and the corresponding allocation method for each task area is the final allocation method.

2. The "negotiation - decision" market auction solution method for multi - robot task allocation according to claim 1, characterized in that: In Step S3, the quote is determined between 85% and 115% of the cost price.

3. The "negotiation - decision" market auction solution method for multi - robot task allocation according to claim 2, characterized in that: In Step S4, 85% to 100% of the cost price represents a lower willingness for this task area, so the priority is lower; 100% to 115% of the cost price represents a higher willingness for this task area, so the priority is higher; Taking the task area as a unit, the higher the quote, the higher the priority will be obtained.

4. A "Negotiation - Decision" market auction solving system for multi - robot task allocation, based on the "Negotiation - Decision" market auction solving method for multi - robot task allocation described in claim 1, characterized in that, Including: Decision-making unit, multiple cooperation units, multiple task area units, initialization unit, data transmission unit, profit and loss calculation unit, quote determination unit, priority determination unit, priority comparison unit, allocation unit, transfer negotiation unit, transfer condition judgment unit, total quote comparison unit; The decision-making unit initializes the information of the cooperation unit and the information of the task area unit through the initialization unit; The decision-making unit transmits the information of the task area unit and the corresponding cost to the cooperation unit through the data transmission unit; The cooperation unit calculates the profit and loss through the profit and loss calculation unit, and transmits the calculation result to the quote determination unit to determine the quote for each task area unit; The quote determination unit transmits each quote information to the decision-making unit for collection, and the decision-making unit determines the priority of the quote of the cooperation unit for each task area unit through the priority determination unit; The decision-making unit randomly selects a task area unit through the allocation unit, determines the cooperation unit with the highest priority for the quote of the task area unit through the priority comparison unit, and allocates the task area unit to the cooperation unit through the allocation unit; The decision-making unit allocates all the task area units to the cooperation unit through the allocation unit; Each cooperation unit sequentially provides the allocated task area unit to other cooperation units through the transfer negotiation unit, and uses the transfer condition judgment unit to determine whether the transfer negotiation unit conducts a transfer; The transfer condition determined by the transfer condition judgment unit is that the selling price is between 85% and 100% of the auction price, and the purchase price of the cooperation unit that finally purchases the task area unit should be higher than the bid price of the cooperation unit for the task area unit in the initial auction; The decision-making unit compares the total bids each time and retains the smallest one.

5. The "Negotiation - Decision" market auction solving system for multi - robot task allocation according to claim 4, characterized in that: The determined bidding unit bids between 85% and 115% of the cost price; 85% to 100% of the cost price means that the cooperation unit hopes to obtain the task area unit by offering a price lower than the cost, that is, the willingness to the task area unit is relatively low; 100% to 115% of the cost price means that the cooperation unit hopes to obtain the task area unit by offering a price higher than the cost, that is, the willingness to the task area unit is relatively high.

6. The "Negotiation - Decision" market auction solving system for multi - robot task allocation according to claim 4, characterized in that: The total bid information stored in the transfer negotiation unit is transmitted to the decision-making unit, and the decision-making unit compares the total bids each time through the total bid comparison unit.

Images