Soft X-ray Circular Reflectivity from Ferromagnetic Transition-Metal Films Near the Brewster's Angle: Theoretical and Numerical X-ray Resonant Magnetic Scattering Study

We first report a novel phenomenon that manifests itself in a colossal difference in soft x-ray reflectivity from ferromagnetic transition-metal films between the left- and right-handed circular polarization (LCP and RCP) modes at a resonance near normal Brewster's angle. Theoretical and numerical studies of sft x-ray resonant magnetic scattering using the circular-polarization-mode basis reveal that this effect arises from a totally destructive interference of photons scattered individually from chargem orbital, and spin degrees of freedom in magnetized thin films that selectively occurs only for one helicity of the opposite circular modes when the required criteria are fulfilled. Across the normal Brewster's angle. the polarization state of scattered soft x-ray is continuously variable from the RCP to the LCP mode (or vice versa) through the linear s polarization mode by changing the incidence angle of linear p-polarized x rays at the resonance.Comment: 16 pages, 3 figures, 1 tabl

Development of Navigation Control Algorithm for AGV Using D* Search Algorithm

In this paper, we present a navigation control algorithm for Automatic Guided Vehicles (AGV) that move in industrial environments including static and moving obstacles using D* algorithm. This algorithm has ability to get paths planning in unknown, partially known and changing environments efficiently. To apply the D* search algorithm, the grid map represent the known environment is generated. By using the laser scanner LMS-151 and laser navigation sensor NAV-200, the grid map is updated according to the changing of environment and obstacles. When the AGV finds some new map information such as new unknown obstacles, it adds the information to its map and re-plans a new shortest path from its current coordinates to the given goal coordinates. It repeats the process until it reaches the goal coordinates. This algorithm is verified through simulation and experiment. The simulation and experimental results show that the algorithm can be used to move the AGV successfully to reach the goal position while it avoids unknown moving and static obstacles. [Keywords— navigation control algorithm; Automatic Guided Vehicles (AGV); D* search algorithm