Multi-modal human-machine communication for instructing robot grasping tasks

@inproceedings{citeulike:713360, abstract = {A major challenge for the realization of intelligent robots is to supply them with cognitive abilities in order to allow ordinary users to program them easily and intuitively. One approach to such programming is teaching work tasks by interactive demonstration. To make this effective and convenient for the user, the machine must be capable of establishing a common focus of attention and be able to use and integrate spoken instructions, visual perception, and non-verbal clues like gestural commands. We report progress in building a hybrid architecture that combines statistical methods, neural networks, and finite state machines into an integrated system for instructing grasping tasks by man-machine interaction. The system combines the GRAVIS-robot for visual attention and gestural instruction with an intelligent interface for speech recognition and linguistic interpretation, and a modality fusion module to allow multi-modal task-oriented man-machine communication with respect to dextrous robot manipulation of objects.}, author = {Mcguire, P. and Fritsch, J. and Steil, J. J. and Rothling, F. and Fink, G. A. and Wachsmuth, S. and Sagerer, G. and Ritter, H. }, citeulike-article-id = {713360}, journal = {Intelligent Robots and System, 2002. IEEE/RSJ International Conference on}, keywords = {grasping, multimodal, robotics}, pages = {1082--1088 vol.2}, posted-at = {2006-06-28 09:06:51}, priority = {2}, title = {Multi-modal human-machine communication for instructing robot grasping tasks}, url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=1043875}, volume = {2}, year = {2002} }

TY - CONF ID - citeulike:713360 L3 - citeulike-article-id:713360 TI - Multi-modal human-machine communication for instructing robot grasping tasks JF - Intelligent Robots and System, 2002. IEEE/RSJ International Conference on VL - 2 SP - 1082 EP - 1088 vol.2 N2 - A major challenge for the realization of intelligent robots is to supply them with cognitive abilities in order to allow ordinary users to program them easily and intuitively. One approach to such programming is teaching work tasks by interactive demonstration. To make this effective and convenient for the user, the machine must be capable of establishing a common focus of attention and be able to use and integrate spoken instructions, visual perception, and non-verbal clues like gestural commands. We report progress in building a hybrid architecture that combines statistical methods, neural networks, and finite state machines into an integrated system for instructing grasping tasks by man-machine interaction. The system combines the GRAVIS-robot for visual attention and gestural instruction with an intelligent interface for speech recognition and linguistic interpretation, and a modality fusion module to allow multi-modal task-oriented man-machine communication with respect to dextrous robot manipulation of objects. KW - grasping KW - multimodal KW - robotics AU - Mcguire, P AU - Fritsch, J AU - Steil, JJ AU - Rothling, F AU - Fink, GA AU - Wachsmuth, S AU - Sagerer, G AU - Ritter, H PY - 2002/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1043875 ER -