This paper describes a Bayesian approach to robot group control applied in industrial applications. The proposed model is based on well-known concepts of Ubiquitous Computing and can enable some degree of contextual p...This paper describes a Bayesian approach to robot group control applied in industrial applications. The proposed model is based on well-known concepts of Ubiquitous Computing and can enable some degree of contextual perception of the 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 to enable the work of a single robot without human intervention by learning Behavioral Patterns of other robots in the group. The described model is designed to be expressive enough to provide adequate level of abstractions needed for making timely appropriate actions and respecting the current application.展开更多
文摘This paper describes a Bayesian approach to robot group control applied in industrial applications. The proposed model is based on well-known concepts of Ubiquitous Computing and can enable some degree of contextual perception of the 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 to enable the work of a single robot without human intervention by learning Behavioral Patterns of other robots in the group. The described model is designed to be expressive enough to provide adequate level of abstractions needed for making timely appropriate actions and respecting the current application.
