Research Of Mine Rescue Multi-robot System Task Allocation Optimization Algorithm

Recently, Robot technology is developing rapidly. Compared with single-robot systems, multi-robot systems have more advantages. But it has become a key problem that whether they can cooperate with each other effectively or not. The research objectives of this paper are a task allocation algorithm based on multi-robot systems. On the basis of deep analysis to the research in and out of China, according to the characteristics of rescue difficulties of mine accident and dynamics, we proposed a task allocation algorithm based on utility valuation .The paper introduces multi-robot systems and thesis of Q-learning and adaptive neural-fuzzy inference system .particularly make a study of utility evaluation algorithm based on Q-learning and adaptive neural-fuzzy inference system which has a good generalization. In this algorithm utility evaluation parameters are modified gradually by on-line learning. We designed different global rewarding functions, which make robots can realize global task allocation and applied in mine rescue. The realization of task election and utility evaluation of are stated in detail in this dissertation. Through the comparison with algorithms ,the feasibility and accuracy of the method is validated . Finally, Design mine rescue robot hardware structure and software process, key parts are mine rescue robot navigation algorithm, and proposed the robot system simulation solutions. it greatly reduced the mine environmental uncertainty and risk. Due to the limitation of condition and time, there are many aspects need to be improved.