TY - GEN
T1 - Probabilistic modeling of human movements for intention inference
AU - Wang, Zhikun
AU - Deisenroth, Marc Peter
AU - Amor, Heni Ben
AU - Vogt, David
AU - Schölkopf, Bernhard
AU - Peters, Jan
N1 - Publisher Copyright:
© 2013 Massachusetts Institute of Technology.
PY - 2013
Y1 - 2013
N2 - Inference of human intention may be an essential step towards understanding human actions and is hence important for realizing efficient human-robot interaction. In this paper, we propose the Intention-Driven Dynamics Model (IDDM), a latent variable model for inferring unknown human intentions. We train the model based on observed human movements/actions. We introduce an efficient approximate inference algorithm to infer the human's intention from an ongoing movement. We verify the feasibility of the IDDM in two scenarios, i.e., target inference in robot table tennis and action recognition for interactive humanoid robots. In both tasks, the IDDM achieves substantial improvements over state-of-The-Art regression and classification.
AB - Inference of human intention may be an essential step towards understanding human actions and is hence important for realizing efficient human-robot interaction. In this paper, we propose the Intention-Driven Dynamics Model (IDDM), a latent variable model for inferring unknown human intentions. We train the model based on observed human movements/actions. We introduce an efficient approximate inference algorithm to infer the human's intention from an ongoing movement. We verify the feasibility of the IDDM in two scenarios, i.e., target inference in robot table tennis and action recognition for interactive humanoid robots. In both tasks, the IDDM achieves substantial improvements over state-of-The-Art regression and classification.
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M3 - Conference contribution
AN - SCOPUS:84959297900
SN - 9780262519687
T3 - Robotics: Science and Systems
SP - 433
EP - 440
BT - Robotics
A2 - Roy, Nicholas
A2 - Newman, Paul
A2 - Srinivasa, Siddhartha
PB - MIT Press Journals
T2 - International Conference on Robotics Science and Systems, RSS 2012
Y2 - 9 July 2012 through 13 July 2012
ER -