Physical Characteristics of the Spectral States of Galactic Black Holes

Using simple analytical estimates we show how the physical parameters characterizing different spectral states of the galactic black hole candidates can be determined using spectral data presently available.Comment: 5 pages, 3 figures, to appear in the Proceedings of 4th Compton Symposium, April 27-30, 1997, Williamsburg, Virginia, US

Cooperative 3D Mapping and Localisation of Multiple Mobile Robots

Developing a coherent and unified approach to localisation and mapping is one of the prerequisites for fully establishing the mobile robotics era in the 21st century. Therefore, this research attempts to address this simultaneous localisation and mapping problem (SLAM) for both a single robot and cooperating multiple robots equipped.with 3D range sensors. To begin with various methods and hardware set-ups for allowing robots to reliably detect each other are explored and tested. Once robots have detected others the question of how their relative pose can be determined most accurately is investigated, especially in the case ·when two corresponding robots detect each other simultaneously. This situation, referred to as mutual localisation, results in reliable and accurate relative pose determination. The second aspect of this work develops hardware mechanisms for mobile robots to obtain 3D information about the environment around them. For robots to rapidly acquire 3D information of their surrounding spatial structure a conventional 2D laser range scanner is augmented with a rotating mirror to build a 3D laser range scanner. A data structure, termed an occupancy list, is devised for efficient probabilistic storing of the 3D map. Algorithms for coherently combining multiple 3D scans from different view points are developed, thus allowing mobile robots to generate an internal representation of their environs.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Cooperative mutual 3D laser mapping and localization

Abstract — A 3D laser scanner is built by adding a rotating mirror to a conventional 2D scanner. The scanners are deployed on four robots to build full 3D representations of an indoor environment. An original representation mechanism referred to as occupancy lists, rather than standard 2D free space grids, is used to maintain the 3D map. Localization is done by extracting horizontal sub-ceiling cross-sections. Taking cross-sections from near the ceiling in this way results in more reliable and time invariant maps. Experimental results show inter-robot sightings and the sharing of map data aid mapping by improving the reliability of localization. Mapping with four robots reduced the average position error from 0.35m for single robot operation to 0.1m when cooperating

Non-cubic occupied voxel lists for robot maps

An alternative to the conventional quantization for occupied voxel lists in both 2D and 3D is presented. The performance metrics of the hexagonal lattice in 2D and the face centred and body centred cubic lattices in 3D are investigated and compared to their square and cubic counterparts. It is found that quantization to alternative lattices yields some improvements. Ultimately, the D3 or face centred cubic lattice is highlighted for its lower quantization error, lower rotation variability and higher order rotational symmetry. It has three times less occupied voxel count pose variability than a standard cubic occupied voxel list. These improvements have implications for SLAM and path planning

Mutual localization and 3D . . .

This paper describes the development of a 3D laser scanner and an approach to 3D mapping and localization. The 3D scanner consists of a standard 2D laser scanner and a rotating mirror assembly. Employing multiple robots and mutual localization local 3D maps are built. Global localization within the maps is performed by extracting a cross-section of the map just below the ceiling and then using an exhaustive search algorithm to enable the merger of multiple local 3D maps. The quality of these maps is such that the poses estimated by this method are accurate to within 0.1m and 1 degree

Fast Circular Landmark Detection for Cooperative Localisation And Mapping

Map building through cooperative localisation (co-location) using circular geometric targets and a SICK laser range scanner is investigated. The tenet of co-location is circle detection in laser range data. Two methods for circle detection, a Range Weighted Circular Hough Transform (RWCHT) and a novel squared-residual voting strategy are compared and their performance assessed. The custom squared-residual voting strategy outperforms the RWCHT in all respects and is subsequently used for localisation and map building. The results include robust continuous localisation at speeds of 0.2m/s with 98% of scan frames used and an error of less than 0.03m. This localisation accuracy helps build maps of 96% quality and occupancy grids of cluttered environments despite the presence of distractors