Before revision:  To better deal with the the problems, we present a  proposal model, named Deep Multimodal Observation Model ( DMOM). DMOM takes a map and a 2D laser scan as inputs and outputs a conditional multimodal probability distribution of the pose, making the samples more focusing on the regions with higher likelihood.
After revision:  To better deal with the the problems, we present a proposal model, named Deep Samplable Observation Model ( DMOM). DMOM takes a map and a 2D laser scan as inputs and outputs a conditional multimodal probability distribution of the pose, making the samples more focusing on the regions with higher likelihood.