Cognitive Robotic Engine for HRI

A "cognitive robotic engine (CRE)" that generates perceptual and action behaviors to select and collect an optimal set of evidences has been introduced previously by the authors. CRE aims at enabling a robot to be capable of dependable and robust recognition and decision under a high level of uncertainty and ambiguity in perception. This paper improves the performance of CRE based on the following expansion: 1) the provision of an evidence structure separately from the internal perceptual processes represented by a precedence graph, such that the contribution of individual evidences to the certainty of the premise pertaining to the given robotic mission can be more clearly defined, and 2) the establishment of a search process for action behaviors based on the overall contribution of the chosen action behaviors to the certainty of the premise pertaining to the given robotic mission. CRE is applied to the two robotic missions, caller identification and caller following, and is evaluated by actual experimentation. The experimental results show the expanded version of CRE results in improvement not only in dependability but also in stability