Abstract
The localization for mine rescue robot in unknown space of coal mine emergency was researched, basing on the requirement of mine rescue robot localization which enters the scene of the coal mine accident, unknown circumstance, the unstructured, non-Gaussian and nonlinear work-space for robot works. The localization using particle filter was proposed to which is applied in mine rescue robot in unknown under-ground space. Meanwhile, focusing on severe particle sample degeneracy in the primary particle filter, an improved particle filter was proposed to reinforce the stability of particle filter. Being compared with localization using extended Kalman filter through simulation experiment, the localization using particle filter is proved to have more locating accuracy in unknown underground space and better computational real-time ability, which solves the pre-localization problem of robot underground.
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