User intentions funneled through a human-robot interface

We describe a method for predicting user intentions as part of a human-robot interface. In particular, we show that funnels, i.e., geometric objects that partition the input space, provide a convenient means for discriminating individual objects and for clustering sets of objects for hierarchical tasks. One advantage of the proposed implementation is that very few parameters need tuning, and a simple heuristic for setting initial parameter values appears promising. We discuss the possibility of adapting the user interface with machine learning techniques, and we illustrate the approach with a humanoid robot performing a variation of a standard peg-insertion task. Keywords Human-robot interaction, telerobotics, predictive display

• Type: Conference
• Year: 2005
• Where: IUI
• Authors: Michael T. Rosenstein, Andrew H. Fagg, Shichao Ou, Roderic A. Grupen
• Keywords: Human-robot Interface, Initial Parameter Values, IUI 2005, Keywords Human-robot Interaction, Software Engineering