Neural Controller for a Mobile Robot in a Nonstationary Enviornment

Recently it has been introduced a neural controller for a mobile robot that learns both forward and inverse odometry of a differential-drive robot through an unsupervised learning-by-doing cycle. This article introduces an obstacle avoidance module that is integrated into the neural controller. This module makes use of sensory information to determine at each instant a desired angle and distance that causes the robot to navigate around obstacles on the way to a final target. Obstacle avoidance is performed in a reactive manner by representing the objects and target in the robot's environment as Gaussian functions. However, the influence of the Gaussians is modulated dynamically on the basis of the robot's behavior in a way that avoids problems with local minima. The proposed module enables the robot to operate successfully with different obstacle configurations, such as corridors, mazes, doors and even concave obstacles.Air Force Office of Scientific Research (F49620-92-J-0499

An information systems assessment framework for agile manufacturing

Turmoil in the business environment is driving manufacturing companies to become agile. Agility means the capability of operating profitably in a competitive environment of continuous and unpredictable changes with information systems regarded as one of its main enablers. The research presented in this work focuses on the assessment of information systems to support agile manufacturing. The assessment framework is constructed upon a series of competitive bases (six) and agility attributes (32) identified in the literature. Other issues included cover the characteristics of the business environment and the evolution/development and infrastructure of information systems. The framework is validated through a survey research instrument and the responses analysed with statistical tests (descriptive statistics, factor analysis, linear regression and reliability). The results of the statistical analysis enabled us to determine the attributes identified as predictors for the set of questions linking information systems and agile manufacturing. Due to the fuzzy nature of assessment of information systems, the complete framework can be presented as a hierarchy where techniques like AHP and fuzzy language sets are applicable. The findings will enable the researchers to clearly identify the trends adopted by manufacturing companies in the utilisation of information systems to gain competitive edge in support of the concept of agile manufacturing