TY - GEN
T1 - Human Manipulation Segmentation and Characterization Based on Instantaneous Work
AU - Remazeilles, Anthony
AU - Rasines, Irati
AU - Fernandez, Asier
AU - McIntyre, Joseph
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
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.
KW - Manipulation segmentation
KW - Teaching by demonstration
UR - https://www.scopus.com/pages/publications/85082137099
U2 - 10.1007/978-3-030-35990-4_28
DO - 10.1007/978-3-030-35990-4_28
M3 - Conference contribution
AN - SCOPUS:85082137099
SN - 9783030359898
T3 - Advances in Intelligent Systems and Computing
SP - 343
EP - 354
BT - Robot 2019
A2 - Silva, Manuel F.
A2 - Luís Lima, José
A2 - Reis, Luís Paulo
A2 - Sanfeliu, Alberto
A2 - Tardioli, Danilo
PB - Springer
T2 - 4th Iberian Robotics Conference, ROBOT 2019
Y2 - 20 November 2019 through 22 November 2019
ER -