TY - GEN
T1 - Motion recognition and generation by combining reference-point-dependent probabilistic models
AU - Sugiura, Komei
AU - Iwahashi, Naoto
PY - 2008/12/1
Y1 - 2008/12/1
N2 - This paper presents a method to recognize and generate sequential motions for object manipulation such as placing one object on another or rotating it. Motions are learned using reference-point-dependent probabilistic models, which are then transformed to the same coordinate system and combined for motion recognition/generation. We conducted physical experiments in which a user demonstrated the manipulation of puppets and toys, and obtained a recognition accuracy of 63% for the sequential motions. Furthermore, the results of motion generation experiments performed with a robot arm are presented.
AB - This paper presents a method to recognize and generate sequential motions for object manipulation such as placing one object on another or rotating it. Motions are learned using reference-point-dependent probabilistic models, which are then transformed to the same coordinate system and combined for motion recognition/generation. We conducted physical experiments in which a user demonstrated the manipulation of puppets and toys, and obtained a recognition accuracy of 63% for the sequential motions. Furthermore, the results of motion generation experiments performed with a robot arm are presented.
UR - http://www.scopus.com/inward/record.url?scp=69549120078&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=69549120078&partnerID=8YFLogxK
U2 - 10.1109/IROS.2008.4651169
DO - 10.1109/IROS.2008.4651169
M3 - Conference contribution
AN - SCOPUS:69549120078
SN - 9781424420582
T3 - 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
SP - 852
EP - 857
BT - 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
T2 - 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
Y2 - 22 September 2008 through 26 September 2008
ER -