Abstract
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.
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Notes
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The experiments were approved by a local Ethics Evaluation Committee.
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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.
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Remazeilles, A., Rasines, I., Fernandez, A., McIntyre, J. (2020). Human Manipulation Segmentation and Characterization Based on Instantaneous Work. In: Silva, M., LuÃs Lima, J., Reis, L., Sanfeliu, A., Tardioli, D. (eds) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing, vol 1092. Springer, Cham. https://doi.org/10.1007/978-3-030-35990-4_28
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