TY - GEN
T1 - A system for learning continuous human-robot interactions from human-human demonstrations
AU - Vogt, David
AU - Stepputtis, Simon
AU - Grehl, Steve
AU - Jung, Bernhard
AU - Ben Amor, Hani
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/21
Y1 - 2017/7/21
N2 - We present a data-driven imitation learning system for learning human-robot interactions from human-human demonstrations. During training, the movements of two interaction partners are recorded through motion capture and an interaction model is learned. At runtime, the interaction model is used to continuously adapt the robot's motion, both spatially and temporally, to the movements of the human interaction partner. We show the effectiveness of the approach on complex, sequential tasks by presenting two applications involving collaborative human-robot assembly. Experiments with varied object hand-over positions and task execution speeds confirm the capabilities for spatio-temporal adaption of the demonstrated behavior to the current situation.
AB - We present a data-driven imitation learning system for learning human-robot interactions from human-human demonstrations. During training, the movements of two interaction partners are recorded through motion capture and an interaction model is learned. At runtime, the interaction model is used to continuously adapt the robot's motion, both spatially and temporally, to the movements of the human interaction partner. We show the effectiveness of the approach on complex, sequential tasks by presenting two applications involving collaborative human-robot assembly. Experiments with varied object hand-over positions and task execution speeds confirm the capabilities for spatio-temporal adaption of the demonstrated behavior to the current situation.
UR - http://www.scopus.com/inward/record.url?scp=85028018545&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85028018545&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2017.7989334
DO - 10.1109/ICRA.2017.7989334
M3 - Conference contribution
AN - SCOPUS:85028018545
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 2882
EP - 2889
BT - ICRA 2017 - IEEE International Conference on Robotics and Automation
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Robotics and Automation, ICRA 2017
Y2 - 29 May 2017 through 3 June 2017
ER -