Abstract
This paper presents a method to estimate the pose of an object inside a robotic hand by exploiting contact and joint position information. Once an initial visual estimation is provided, a Bootstrap Particle Filter is used to evaluate multiple hypothesis for the object pose. The function used to score the hypothesis considers feasibility and physical meaning of the contacts between the object and the hand. The method provides a good estimation of in-hand pose for different 3D objects.
This work has received funding from the Spanish Ministry of Economy, Industry and Competitiveness under the projects DPI2013-47944-C4-3-R and DPI2016-80077-R, and the RoboCity2030-III-CM project, stage III, S2013/MIT-2748), cofunded by “Programas de Actividades I+D en la Comunidad de Madrid”, and by Structural Funds of the EU.
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Álvarez, D., Roa, M.A., Moreno, L. (2018). Tactile-Based In-Hand Object Pose Estimation. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-70836-2_59
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DOI: https://doi.org/10.1007/978-3-319-70836-2_59
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