Three-Dimensional Path Planning of Unmanned Aerial Vehicles Using Particle Swarm Optimization

Military operations are turning to more complex and advanced automation technology for minimum risk and maximum efficiency. A critical piece to this strategy is unmanned aerial vehicles (UAVs). UAVs require the intelligence to safely maneuver along a path to an intended target, avoiding obstacles such as other aircrafts or enemy threats. Often automated path planning algorithms are employed to specify targets for a UAV to fly to. To date, path-planning algorithms have been limited to two-dimensional problem formulations. This paper presents a unique three-dimensional path planning problem formulation and solution approach using Particle Swarm Optimization (PSO). The problem formulation was designed to minimize risk due to enemy threats while simultaneously minimizing fuel consumption. The initial design point is a straight path between the current position and the desired target. Using PSO, an optimized path is generated through B-spline curves. The resulting paths can be optimized with a preference towards maximum safety, minimum fuel consumption or a combination of the two. The problem formulation and solution implementation is described along with the results from several simulated scenarios.This is a conference proceeding from AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference (2006): 1, doi:10.2514/6.2006-6995. Posted with permission.</p

Familial influences on sustained attention and inhibition in preschoolers

Background: In this study several aspects of attention were studied in 237 nearly 6-year-old twin pairs. Specifically, the ability to sustain attention and inhibition were investigated using a computerized test battery (Amsterdam Neuropsychological Tasks). Furthermore, the Teacher's Report Form (TRF) was filled out by the teacher of the child and the attention subscale of this questionnaire was analyzed. Methods: The variance in performance on the different tasks of the test battery and the score on the attention scale of the TRF were decomposed into a contribution of the additive effects of many genes (A), environmental effects that are shared by twins (C) and unique environmental influences not shared by twins (E) by using data from MZ and DZ twins. Results: The genetic model fitting results showed an effect of A and E for the attention scale of the TRF, and for some of the inhibition and sustained attention measures. For most of the attention variables, however, it was not possible to decide between a model with A and E or a model with C and E. Time-on-task effects on reaction time or number of errors and the delay after making an error did not show familial resemblances. A remarkable finding was that the heritability of the attention scale of the TRF was found to be higher than the heritability of indices that can be considered to be more direct measures of attention, such as mean tempo in the sustained attention task and response speed in the Go-NoGo task. Conclusion: In preschoolers, familial resemblances on sustained attention and inhibition were observed. © Association for Child Psychology and Psychiatry, 2004

Three Dimensional Multi-Objective Path Planning of Unmanned Aerial Vehicles Using Particle Swarm Optimization

Military operations are turning to more complex and advanced automation technology for minimum risk and maximum efficiency. A critical piece to this strategy is unmanned aerial vehicles (UAVs). UAVs require the intelligence to safely maneuver along a path to an intended target, avoiding obstacles such as other aircrafts or enemy threats. Often automated path planning algorithms are employed to specify targets for a UAV to fly to. To date, path-planning algorithms have been limited to two-dimensional problem formulations. This paper presents a unique three-dimensional path planning problem formulation and solution approach using Particle Swarm Optimization (PSO). The problem formulation was designed to minimize risk due to enemy threats and also to minimize fuel consumption incurred by deviating from the original path. In addition, a third objective in the problem formulation takes into account reconnaissance targets. The initial design point is defined as the original path of the UAV. Using PSO, alternate paths are generated using B-spline curves, optimized based on preferences set for the three objectives. The resulting paths can be optimized with a preference towards maximum safety, minimum fuel consumption, or target reconnaissance. The problem formulation and solution implementation is described along with the results from several simulated scenarios. I

Polarized inelastic neutron scattering of the partially ordered Tb2Sn2O7

We present inelastic neutron scattering results on the geometrically frustrated pyrochlore Tb2Sn2O7. At high temperature T gt;50K, this system resembles the cooperative paramagnet Tb2Ti2O7, while at low temperature T 60mK, it displays remarkably different behavior. Powder neutron scattering, susceptibility and specific heat techniques have shown that below 0.87K Tb2Sn2O7 enters a partially ordered state that is characterized by two sublattice ferrimagnetic long range order which coexists with paramagnetic spin components. We show that i the low temperature state produces a large internal field and collective excitations and ii the coexisting paramagnetic state persists down to 0.1K, with spins fluctuation at a rate greater than 0.04 THz, resulting in a diffuse magnetic background to the diffraction patterns. A low lying excitation at 1.2meV partially softens as short range correlations build up while cooling in the paramagnetic stat