RT Conference Proceedings
T1 Human Manipulation Segmentation and Characterization Based on Instantaneous Work
A1 Remazeilles, Anthony
A1 Rasines, Irati
A1 Fernandez, Asier
A1 McIntyre, Joseph
A2 Silva, Manuel F.
A2 Luís Lima, José
A2 Reis, Luís Paulo
A2 Sanfeliu, Alberto
A2 Tardioli, Danilo
AB This paper is related to the observation of human operator manipulating objects for teaching a robot to reproduce the action. Assuming the robotic system is equipped with basic manipulation skills, we focus here on the automatic segmentation of the observed manipulation, for extracting the relevant key frames in which the manipulation is best described. The segmentation method proposed is based on the instantaneous work, and presents the advantage of not depending on the force and pose sensing locations. The proposed approach is experimented with two different manipulation skills, sliding and folding, under different settings.
PB Springer
SN 9783030359898
SN 2194-5357
YR 2020
FD 2020
LK https://hdl.handle.net/11556/1724
UL https://hdl.handle.net/11556/1724
LA eng
NO Remazeilles , A , Rasines , I , Fernandez , A & McIntyre , J 2020 , Human Manipulation Segmentation and Characterization Based on Instantaneous Work . in M F Silva , J Luís Lima , L P Reis , A Sanfeliu & D Tardioli (eds) , Robot 2019 : 4th Iberian Robotics Conference - Advances in Robotics . Advances in Intelligent Systems and Computing , vol. 1092 AISC , Springer , pp. 343-354 , 4th Iberian Robotics Conference, ROBOT 2019 , Porto , Portugal , 20/11/19 . https://doi.org/10.1007/978-3-030-35990-4_28
NO conference
NO Publisher Copyright: © 2020, Springer Nature Switzerland AG.
NO Acknowledgements. Supported by the Elkartek MALGUROB and the SARAFun project under the European Union’s Horizon 2020 research & innovation programme, grant agreement No. 644938. The authors would like to thank Dr. Pierre Barralon for the fruitfull discussions that led to the segmentation approach presented here. Supported by the Elkartek MALGUROB and the SARAFun project under the European Union?s Horizon 2020 research & innovation programme, grant agreement No. 644938. The authors would like to thank Dr. Pierre Barralon for the fruitfull discussions that led to the segmentation approach presented here.
DS TECNALIA Publications
RD 30 jul 2024