Abstract— We consider the problem of autonomously estimating position and orientation of an object from tactile data. When initial uncertainty is high, estimation of all six para...
Anna Petrovskaya, Oussama Khatib, Sebastian Thrun,...
— In this paper we address the problem of generating a motion strategy to find an object in a known 3-D environment as quickly as possible on average. We use a sampling scheme t...
Alejandro Sarmiento, Rafael Murrieta-Cid, Seth Hut...
We propose a selection scheme called Fitness-based Neighbor Selection (FNS) for multimodal optimization. The FNS is aimed for ill-scaled and locally multimodal domain, both found ...
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
This paper presents an optimized Hill Climbing algorithm to select a subset of features for handwritten character recognition. The search is conducted taking into account a random ...
Carlos M. Nunes, Alceu de Souza Britto Jr., Celso ...