Investigating long-term fatal corrosion of turquoise lead-potassium historic glass beads, we have detected micro and nano crystallites of orthorhombic KSbOSiO<sub>4</sub> (KSS) in glass. We have come to conclusion that KSS precipitates and their clusters give rise to internal glass corrosion. K and Sb being glass dopants form KSS crystallites during glass melt cooling; tensile strain arising in the glass matrix during cooling gives rise to glass cracking and eventually to its rupture and formation of heterogeneous grains. The strain-induced diffusion of impurities, resembling internal gettering in the Si technology, explains changes in glass color. We have also detected Pb<sub>2</sub>Fe<sub>0.5</sub>Sb<sub>1.5</sub>O<sub>6.5</sub> nano crystallites in stable yellow lead glass beads. The number density and the sizes of these crystallites are much less than those of the KSS crystallites in turquoise lead-potassium glass, they do not form large clusters; internal cracks also has not been observed in this glass. This may explain the stability of yellow lead glass. The study may be useful for predicting long-term stability of technical glasses as well as for synthesis of nano-KSS/glass composites.
This paper presents a comparison of four most recent ROS-based monocular SLAM-related methods: ORB-SLAM, REMODE, LSD-SLAM, and DPPTAM, and analyzes their feasibility for a mobile robot application in indoor environment. We tested these methods using video data that was recorded from a conventional wide-angle full HD webcam with a rolling shutter. The camera was mounted on a human-operated prototype of an unmanned ground vehicle, which followed a closed-loop trajectory. Both feature-based methods (ORB-SLAM, REMODE) and direct SLAMrelated algorithms (LSD-SLAM, DPPTAM) demonstrated reasonably good results in detection of volumetric objects, corners, obstacles and other local features. However, we met difficulties with recovering typical for offices homogeneously colored walls, since all of these methods created empty spaces in a reconstructed sparse 3D scene. This may cause collisions of an autonomously guided robot with unfeatured walls and thus limits applicability of maps, which are obtained by the considered monocular SLAM-related methods for indoor robot navigation.