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The second step for lunar exploration of China has been completed already, the probe "Chang'e-3" successfully landed on the moon, including a lander and a lunar rover. The third step of the project is to achieve automated sampling of lunar regolith through a drilling and coring device. On the moon, lunar regolith and lunar rock may be encountered randomly along the longitudinal direction. Due to the indeterminable drilling environments for the sampling device, the automated control becomes very crucial in the drilling process. This paper proposed an adaptive neuro-fuzzy inference system (ANFIS) based control strategy to tackle the complex drilling media beneath lunar surface. The network is trained through typical lunar regolith simulants and lunar rock simulants, with high identification ratio. A multi-layered drilling medium is built with lunar regolith simulant and lunar rock simulant for drilling experimental test. Experiments indicate that the ANFIS based control strategy can adapt to the complex environment well.

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