 Considering that learning based Samplable Observation Model may fail to capture the true pose sometimes, we furthermore propose the Adaptive Mixture MCL , which adaptively selects updating mode for each particle to tolerate this situation.
<meaning-changed>  Considering that learning based Samplable Observation Model may fail to capture the true pose sometimes, we furthermore propose the Adaptive Mixture MCL , which adaptively selects updating mode for each particle to tolerate this situation.
 Considering that learning based Samplable Observation Model may fail to capture the true pose sometimes, we furthermore propose the Adaptive Mixture MCL (AdaM MCL), which deploys a trusty mechanism to adaptively select updating mode for each particle to tolerate this situation.