Antoni Grau-Saldes

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Monocular simultaneous localization and mapping (SLAM) techniques implicitly estimate camera ego-motion while incrementally building a map of the environment. In monocular SLAM, when the number of features in the system state increases, maintaining a real-time operation becomes very difficult. However, it is easy to remove old features from the state to(More)
Non-speech audio is a non-explored characteristic in robot localization but due to its potentiality it can yield a valuable information together with other sensorial systems. In this work, a novel robot localization method is proposed based on audio signal pattern recognition with extracted features from signal identification. To reinforce the localization,(More)
In this paper a novel method for indexing views of 3D objects is presented. The topological properties of the regions of the views of a set of objects are used to define an index based on the region connection calculus and oriented matroid theory. Both are formalisms for qualitative spatial representation and reasoning and are complementary in the sense(More)
Non-speech audio gives important information from the environment that can be used in robot navigation altogether with other sensor information. In this article we propose a new methodology to study non-speech audio signals with pattern recognition techniques in order to help a mobile robot to self-localize in space domain. The feature space will be built(More)
This work presents a variant approach to the monocular SLAM problem focused in exploiting the advantages of a human-robot interaction (HRI) framework. Based upon the delayed inverse-depth feature initialization SLAM (DI-D SLAM), a known monocular technique, several but crucial modifications are introduced taking advantage of data from a secondary monocular(More)
Recently, the unified inverse depth parametrization has shown to be a good option for challenging monocular SLAM problem, in a scheme of EKF for the estimation of the stochastic map and camera pose. In the original approach, features are initialized in the first frame observed (undelayed initialization), this aspect has advantages but also some problems. In(More)