Probabilistic Approach to Robot Group Control

Abstract

The objective of this paper is to discuss the probabilistic part of the model for robot group control applied in industrial applications. The proposed model is based on well-known concepts of Ubiquitous Computing [1] and enables contextual perception of a working environment. Compared with classical industrial robots, usually preprogrammed for a limited number of operations / actions, the system based on this model can react in uncertain situations and scenarios. The model combines ontology to describe the specific domain of interest and decision–making mechanisms based on Bayesian Networks (BN) to enable the work of a single robot without human intervention by learning Behavioral Patterns (BP) of other robots in the group.