Multi-robot distributed task assignment formation method facing dynamic task

Abstract

The invention provides a multi-robot distributed task assignment formation method facing a dynamic task. The method comprises steps that the factors and difficulties that need to be considered in the task assignment are analyzed according to the state change of the task point in the environment map; when the task point occurs, the task assignment scheme is generated based on the multi-stage auction algorithm; and the robot performs the task according to the task assignment scheme. The method solves the problem of dynamic task assignment in the environment. The traditional auction algorithm adopts a one-time distribution to solve the given task, and there are great limitations in the face of dynamic tasks. The invention uses the resources of the robot to simulate the method on the VC ++ and Csharp platforms through a plurality of auctions and with the time optimal as the purpose. Through a large number of experimental simulation results, the improved auction algorithm is more effective than the traditional auction algorithm and can solve the dynamic task in the environment well, can meet the real-time demand through multiple assignments, and can give the approximately optimal solution.

Description

technical field [0001] The present invention relates to the technical field of robot intelligent auction algorithms, and more specifically, relates to a dynamic task-oriented multi-robot distributed task allocation and formation method. Background technique [0002] With the deepening of people's understanding of artificial intelligence and complex systems, robot systems have good application prospects in construction, military, fire protection, industrial production and other fields. However, in the current multi-robot system, the number of tasks is large, the task points contain complex information, and there are many participating robots. The calculation cost of the global search algorithm increases exponentially, which makes it difficult for the global search algorithm to find the optimal solution for the task allocation problem within the specified time. Excellent solution. Therefore, the global search algorithm is not suitable for solving large-scale multi-agent dynam...

AI Technical Summary

Problems solved by technology

However, in the face of a large number of task points and dynamic changes, there are great defects. It is impossible to implement more scheduling, cannot meet the needs of real-time performance, and cannot obtain ideal results.

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