As a special application scenario, the data collected by wireless sensor networks of coal mine robot is from vital and dangerous environment. Therefore, the nodes need to work as long as possible. In order to efficiently utilize the node energy of wireless sensor network, this paper proposes a self-organizing routing method for wireless sensor networks based on Q-learning. The method takes many factors into account, such as the hop number, distance, residual energy, and node communication loss and energy. Each node of the wireless sensor networks is mapped into an Agent. Periodic training is carried out to optimize the route choice. Each Agent chooses the optimal path for data transmission according to the calculated Q evaluation value. Simulation results show that the self-organizing sensor networks using Q-learning can balance the energy consumption of the nodes and prolong the lifetime of the networks.
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