Neural maps project data from an input space onto a neuron position in a (often lower dimensional) output space grid in a neighborhood preserving way, with neighboring neurons in the output space responding to neighboring data points in the input space. A map-learning algorithm can achieve an optimal neighborhood preservation only, if the output space topology roughly matches the effective stru...

Simultaneous Localization and Mapping (SLAM) is one of the classical problems in mobile robotics. The task is to build a map of the environment using on-board sensors while at the same time localizing the robot relative to this map. Rao-Blackwellized particle filters have emerged as a powerful technique for solving the SLAM problem in a wide variety of environments. It is a well-known fact for ...

In this paper we introduced a novel gas distribution mapping algorithm, Bayesian Spatial Event Distribution (BASED), that, instead of modeling the spatial distribution of the gas concentration, models the spatial distribution of events of detection and non-detection of a target gas. The proposed algorithm is based on the Bayesian Inference framework and models the likelihood of events at a cert...

Simultaneous Localization and Mapping (SLAM) is one of the classical problems in mobile robotics. The task is to build a map of the environment using on-board sensors while at the same time localizing the robot relative to this map. Rao-Blackwellized particle filters have emerged as a powerful technique for solving the SLAM problem in a wide variety of environments. It is a well-known fact for ...

Reserve design is concerned with optimal selection of sites for new conservation areas. Spatial reserve design explicitly considers the spatial pattern of the proposed reserve network and the effects of that pattern on reserve cost and/or ability to maintain species there. The vast majority of reserve selection formulations have assumed a linear problem structure, which effectively means that t...

The knowledge of distribution grid models, including topologies and line impedances, is essential for monitoring, control protection. However, such information often unavailable, incomplete or outdated. increasing deployment smart meters (SMs) provides a unique opportunity to tackle this issue. This paper proposes two-stage framework modeling using SM data. In the first stage, network topology ...

An efficient and accurate LiDAR place recognition methodology is proposed for vehicle localization. First, the Iris-LOAM to overcome disadvantages of low accuracy loop-closure detection efficiency map construction in existing LOAM-series methods. The method integrates LiDAR-Iris global descriptor Normal Distribution Transform (NDT) registration into module Odometry Mapping (LOAM), thereby impro...

We propose a novel, hybrid SLAM system to construct a dense occupancy grid map based on sparse visual features and dense depth information. While previous approaches deemed the occupancy grid usable only in 2D mapping, and in combination with a probabilistic approach, we show that geometric SLAM can produce consistent, robust and dense occupancy information, and maintain it even during erroneou...