engleski

A context-aware approach in realization of socially intelligent industrial robots

Contemporary industrial environments are usually constrained or limited in order to fit a fast, cheap and non-error prone production. Human-like system capabilities are not generally desirable there. But, recent trends in industrial robotics demand robust, flexible and efficient robots with a certain level of autonomy. Therefore, new and different approaches and perspectives in designing of industrial facilities are required. This paper reveals how a context-based reasoning can be used to achieve an intelligent robot group behavior. In order to achieve adaptivity, self- recovery or scalability of the system, a COgnitive MOdel for the Robot group control (COMOR) is developed. COMOR can be understood as an interpreter used to transform high-level context to low-level data, allowing machines to make context-based decisions. COMOR has three main parts and relies on a simulated Social Capital phenomenon as a feature of people. The first part is used to collect significant information from the environment. The second part is used to provide a set of possible solutions respecting the semantic domain description. The last part of COMOR is used to provide a behavioral component ensuring an optimal solution to given environmental conditions.

Cognitive robotics ; Context-awareness ; Probabilistic graphical models ; Ontology ; Ubiquitous computing

Rad je vezan za istraživanje u sklopu projekta ACRON - Novi koncept primijenjene kognitivne robotike u kliničkoj neuroznanosti, broj projekta 4192. Istraživački projekt ACRON je financiran od strane Hrvatske zaklade za znanost.