|
| |
| M.T. Rosenstein, A.H. Fagg, S. Ou, and R.A. Grupen. User intentions funneled through a human-robot interface. In Proceedings of the 10th International Conference on Intelligent User Interfaces, 257-259, 2005. | |
| Abstract: 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 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 peginsertion task. | |
| Download: pdf (2.8MB) | |
| See also: | |
|
Remote supervisory control of a humanoid robot | |
|
Robot learning with predictions of
operator intent | |
|
Supervised actor-critic reinforcement
learning | |
|
updated 13-Dec-2005 mtr@cs.umass.edu |