Dynamic graph-based search in unknown environments

A novel graph-based approach to search in unknown environments is presented. A virtual geometric structure is imposed on the environment represented in computer memory by a graph. Algorithms use this representation to coordinate a team of robots (or entities). Local discovery of environmental features cause dynamic expansion of the graph resulting in global exploration of the unknown environment. The algorithm is shown to have O(k.nH) time complexity, where nH is the number of vertices of the discovered environment and 1 <= k <= nH. A maximum bound on the length of the resulting walk is given

Editorial

An essential property of a high-quality metallic nanofilm is the quantization of the electron spectrum due to dimensional confinement in one direction. Quantum confinement has a substantial impact on the superconducting characteristics and leads to quantum-size variations of the critical temperature Tc with film thickness. We demonstrate that the Bogoliubov-de Gennes equations are able to describe the thickness-dependent Tc in nanofilms, and our results are in good agreement with recent experimental data on ${\rm Pb}$ flat terraces grown on silicon (Science, 306 (2004) 1915 and Nature Phys., 2 (2006) 173). We predict that the quantum-size oscillations of $T_{\rm c}$ will be more pronounced for ${\rm Al}$