Juan Manuel Sáez

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The aquatic realm is ideal for testing autonomous robotic technology. The challenges presented in this environment are numerous due to the highly dynamic nature of the medium. Applications for underwater robotics include the autonomous inspection of coral reef, ships, pipelines, and other environmental assessment programs. In this paper we present current(More)
In this work we have embodied a full 6DOF SLAM solution into a wearable stereo device working in near realtime. In order to serve on-line metric (map) and positional (localization) to the blind or visually impaired we introduce three basic elements: (i) a real-time egomotion estimation integrating 3D and 2D (appearance) information; (ii) a randomized(More)
In this paper, we present a novel approach for aerial obstacle detection using a stereo vision wearable device in the context of the visually impaired assistance. This kind of obstacles are specially dangerous because they could not be detected by the walking stick. The algorithm maintains a local 3D map of the vicinity of the user, which is estimated(More)
We present a stereo-based approach for building 3D maps. First, the best local alignment between successive point clouds is computed by a fast ego-motion/action-estimation algorithm which relies on an incremental matches filtering process followed by energy minimization. Then, a quasi-random updating algorithm, a kind of multi-view ICP, minimizes the global(More)
In this paper we present an information-based approach to solve the SLAM problem using stereo vision. This approach results for an improvement, in terms of both efficiency and robustness, of our early multi-view ICP randomized algorithm. Instead of minimizing an ICP-based cost, we propose the minimization of the entropy of the 2D distribution induced by the(More)
In this paper, we propose and validate an entropy minimization algorithm for solving the SLAM problem in the 6DOF case with semi-sparse (stereo) data. The proposed SLAM solution relies on both an efficient and robust strategy for egomotion estimation and an effective global rectification strategy. Our global rectification method is scalable because it(More)
In this paper, we present a novel approach to computing ceiling mosaics based on Information Theory. The only sensor of the robot is a digital camera oriented to the ceiling of the map, which is used to approximate the Simultaneous Localization and Mapping (SLAM) problem. We have divided the algorithm into two steps: (i) action estimation, which(More)
In this paper, we address the problem of estimating the parameters of Gaussian mixture models. Although the expectation-maximization (EM) algorithm yields the maximum-likelihood (ML) solution, its sensitivity to the selection of the starting parameters is well-known and it may converge to the boundary of the parameter space. Furthermore, the resulting(More)
In this paper we address the problem of estimating the parameters of a Gaussian mixture model. Although the EM algorithm yields the maximum-likelihood solution it requires a careful initialization of the parameters and the optimal number of kernels in the mixture may be unknown beforehand. We propose a criterion based on the entropy of the pdf (probability(More)