Multi Body Kalman Filtering with Articulation Constraints for Humanoid Robot Pose and Motion Estimation
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.
KeywordsRigid Body Motion Estimation Humanoid Robot Biped Robot Rotation Error
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