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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 an 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 a simple parametric model can be used to specify the shape of a funnel, and a straightforward heuristic for setting initial parameter valuesdoi:10.1145/1040830.1040888 dblp:conf/iui/RosensteinFOG05 fatcat:xpayvgghkrfvjapkixobcbf67e