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This paper explores the fusion of inertial information with vision for 3D reconstruction. A method is proposed for vertical line segment detection and subsequent local geometric map building. Visual and inertial sensing are two sensory modalities that can be explored to give robust solutions on image segmentation and recovery of 3D structure from images, increasing the capabilities of autonomous vehicles and enlarging the application potential of vision systems. From the inertial sensors, a camera stereo rig, and a few system parameters we can recover the 3D parameters of the ground plane and vertical lines. The homography between stereo images of ground points can be found. By detecting the vertical line segments in each image, and using the homography of ground points for the foot of each segment, the lines can be matched and reconstructed in 3D. The mobile robot then maps the detected vertical line segments in a world map as it moves. To build this map an outlier removal method is implemented and a statistical approach used, so that a simplified metric map can be obtained for robot navigation.

An investigation on the crystallisation of a whitlockite type orthophosphate phase in a calcium phosphosilicate glass frit with the molar composition (3CaO.P 2 O 5 ) 20 (SiO 2 ) 35 (MgO) 38.354 (K 2 O) 6.646 was made.Isothermal heat treatments at different temperatures combined with XRD and SEM analysis of the glass ceramics have shown that in glass frits of this composition the whitlockite type orthophosphate phase, Ca 9 MgK(PO 4 ) 7 develops from earlier crystalline phosphate phase precursors, namely from oxyapatite (OAp), the ideal composition being Ca 5 (PO 4 ) 3 O. This OAp phase seems to evolve from a previous tricalcium phosphate phase, Ca 3 (PO 4 ) 2 (TCP).

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