In this paper, a concept for articulated rigid body state estimation is proposed. The articulated body, for instance a humanoid robot, is modeled in a maximal coordinate formulation and the articulations between the rigid bodies as nonlinear position and linear motion constraints. At first, the individual state of each particular rigid body is estimated with a Kalman filter, which leads to an unconstrained state estimate. Subsequently, the correct state estimate for the articulated rigid body is derived by projecting the unconstrained estimate onto the constraint surface. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Hauschildt, D., Kerner, S., Tasse, S., & Urbann, O. (2012). Multi body kalman filtering with articulation constraints for humanoid robot pose and motion estimation. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7416 LNCS, 415–426. https://doi.org/10.1007/978-3-642-32060-6_35
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