Before revision:  The popular method, Monte Carlo Localization (MCL) addresses the problem by sampling uniformly ] over the state space , which is unfortunately inefficient when the environment is large .
After revision:  The popular method, Monte Carlo Localization (MCL) addresses the problem by sampling uniformly ]. However, traditional MCL can only sample from a uniform distribution over the state space , which is unfortunately inefficient when the environment is large .