No abstract

We present a genetic algorithm-based method to optimize trajectory planning for mini-robotic tasks. This is done by codibing a number of motion primitive parameters into computational chromosomes. Each trajectory is composed of aji.xed number A' of straight segments. We search with a genetic algorithm the length and direction parameters of the N path segments that let us to arrive a target position from the current robot position. We show design choices of the genetic operators (selection, mutation andjitnessjimction) used in our genetic algorithm implementation. We present simulotions of our method and experimentation on a mini-roboticplafform is implemented.

No abstract

We present in this paper a genetic algorithm (GA) approach to solve 2-D bin packing problems of polygonal shapes on a rectangular canvas. We present how to encode shape parameters and a fitness function based on a the medial axis transform (MAT) to evaluate individuals of a genetic algorithm population. Some test and results of our experimentation are presented.

Measurements of line intensity ratios have been used in astronomy to determine physical properties of plasmas such as density and temperature. Herein, this procedure was applied to monitor thin film growth during plasma-assisted deposition and useful information about the plasma was obtained. The aim of this study was to monitor plasma variations during deposition, using wide field optical spectroscopy, and to establish a relationship with thin film stoichiometry using spectroscopic ellipsometry. With this purpose, inhomogeneous SiOxNy thin films were grown by dc magnetron sputtering.