A dynamic task-oriented multi-intelligence robot task allocation method

Abstract

The invention provides a dynamic task-oriented multi-intelligence robot task allocation method, which mainly solves the multi-task allocation problem that task state quantities have time-varying characteristics. Including: first obtain the dynamic task characteristic parameters, combined with the intelligent robot ability parameters, to establish the characteristic equation of the state quantity of the task point; according to the characteristic equation, design the intelligent robot income function; secondly, according to the income function, design the genetic algorithm fitness function; further design the genetic algorithm The difference selection operator and the local mutation operator are proposed, and the algorithm repair strategy is proposed; finally, the task allocation plan of the intelligent robot is generated by using the genetic algorithm, and the multi-task allocation is completed. The task allocation method proposed by the present invention aims to obtain the maximum benefit of the system, realizes the rapid allocation of dynamic multi-tasks, solves the problem of chromosome deadlock in the algorithm, and avoids the search from falling into local optimum; through the multi-stage allocation strategy, the system can be fully mobilized Intelligent robots participate in the completion of tasks and improve the overall performance of the system.

Description

technical field [0001] The invention relates to the technical field of intelligent robot task allocation algorithms, and more particularly, relates to a dynamic task-oriented multi-intelligent robot task allocation method. Background technique [0002] In recent years, with the deepening of people's understanding of artificial intelligence and complex systems, the research in the field of intelligent multi-robot systems has achieved rich results in both theory and practical systems. Intelligent robots can replace humans to help us in some harsh environments. To complete certain tasks, such as aerospace, deep sea exploration, expedition and disaster relief, etc., these environments are often accompanied by toxic, anaerobic, high temperature and high pressure, strong radiation and other substances harmful to the human body, which exceed the limit that humans can bear. [0003] In the current multi-robot system, the number of tasks is large and the tasks change dynamically. Whe...

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Problems solved by technology

[0003] In the current multi-robot system, the number of tasks faced is large and the tasks change dynamically. When the traditional genetic algorithm solves such dynamic task allocation problems, it will cause deadlocks, easily fall into local optimum, and cannot implement multiple allocations. It is a waste of intelligence. At the same time, it cannot meet the needs of real-time performance, which seriously affects the completion of tasks.

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