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.
CITATION STYLE
Álvarez, D., Roa, M. A., & Moreno, L. (2018). Tactile-Based In-Hand Object Pose Estimation. In Advances in Intelligent Systems and Computing (Vol. 694, pp. 716–728). Springer Verlag. https://doi.org/10.1007/978-3-319-70836-2_59
Mendeley helps you to discover research relevant for your work.