Simulation-based physics reasoning for consistent scene estimation in an HRI context

More recently, In [4] and [5], optimal distributed estima- tion algorithms which are for finding the optimal linear combination of the local estimates weighted by matrices and

The closed-form expressions for the optimal tuning of the AR(2) parameters and mean square error (MSE) performance have been first established as a function of the second and

EMSO is the European counterpart to similar large-scale systems in various stages of development around the world (see Favali et al., 2010): United States (Ocean Observatories

R´ ESUM´ E: Dans ce travail sur le d´ebruitage d’image, nous pr´esentons un nouveau type d’estimateur par patchs inspir´e de la m´ethode NL-Means propos´ee par Buades, Coll

Using a sensor bio-inspired from electric fish, we shown through experiments: first, that small objects can be recon- structed and localized as equivalent spheres; second, that

This paper introduces a new method on which the system parameters are es- timated through an IPKF and the Kriging step is not only used for the interpolation of data but also to infer

This contextual appearance information is extracted from moving image regions and used to train on-line a discriminative binary classifier that, in each video frame, detects the

The model is further simplified so as to apply Kalman filter approach to es- timate displacement and unknown parameters (material properties, e.g., friction angle and