Task allocation of handling robot in textile workshop based on multi-agent game theory

A distributed autonomous decision-making framework was proposed based on multi-agent game theory. The framework is used to solve the problems of handling robot in the process of intelligent textile production and processing, which are large-scale and complex dynamic task allocation problems. To start with, the task model was established according to the actual task environment of textile production. Taking into account of the task distance and time priority, the target utility function of the agent was then used as the policy selection basis, and the equilibrium theory of the game was introduced to solve the problem. Eventually, the decision framework was verified by experiments. The experimental results show that the global optimal solution of the task allocation in this decision framework can be better achieved in comparison to the similar distributed task allocation algorithms. In summary, the proposed algorithm has high scalability, good robustness, and convergence performance. Furthermore, the proposed algorithm has excellent performance for dynamic task allocation. Copyright No content may be reproduced or abridged without authorization.