https://hdl.handle.net/11000/36838 2026-04-06T11:08:00Z https://hdl.handle.net/11000/36841 Título : Triplet Neural Networks for the Visual Localization of Mobile Robots Autor : Alfaro, Marcos; Cabrera, Juan José; Jiménez, Luis Miguel; Reinoso, Óscar; Payá, Luis Resumen : Triplet networks are composed of three identical convolutional neural networks that function in parallel and share their weights. These architectures receive three inputs simultaneously and provide three different outputs, and have demonstrated to have a great potential to tackle visual localization. Therefore, this paper presents an exhaustive study of the main factors that influence the training of a triplet network, which are the choice of the triplet loss function, the selection of samples to include in the training triplets and the batch size. To do that, we have adapted and retrained a network with omnidirectional images, which have been captured in an indoor environment with a catadioptric camera and have been converted into a panoramic format. The experiments conducted demonstrate that triplet networks improve substantially the performance in the visual localization task. However, the right choice of the studied factors is of great importance to fully exploit the potential of such architectures 2025-07-11T11:54:16Z https://hdl.handle.net/11000/36840 Título : Evaluation of Open-Source OCR Libraries for Scene Text Recognition in the Presence of Fisheye Distortion Autor : Flores, María; Valiente, David; Alfaro, Marcos; Fabregat-Jaénn, Marc; Payá, Luis Resumen : Due to the rich and precise semantic information that text provides, scene text recognition is relevant in a wide range of vision-based applications. In recent years, the use of vision systems that combine a camera and a fisheye lens is common in a variety of applications. The addition of a fisheye lens has the great advantage of capturing a wider field of view, but this causes a great deal of distortion, making certain tasks challenging. In many applications, such as localization or mapping for a mobile robot, the algorithms work directly with fisheye images (i.e. distortion is not corrected). For this reason, the principal objective of this work is to study the effectiveness of some OCR (Optical Character Recognition) open-source libraries applied to images with fisheye distortion. Since no scene text dataset of this kind of image has been found, this work also generates a synthetic image dataset. A fisheye model which varies some parameters is applied to standard images of a benchmark scene text dataset to generate the proposed dataset. 2025-07-11T11:52:10Z https://hdl.handle.net/11000/36839 Título : Augmented Feasibility Maps: A Simultaneous Approach to Redundancy Resolution and Path Planning Autor : Fabregat-Jaén, Marc; Peidró, Adrián; González-Amorós, Esther; Flores, María; Reinoso, Oscar Resumen : Redundant robotic manipulators are capable of performing complex tasks with an unprecedented level of dexterity and precision. However, their redundancy also introduces significant computational challenges, particularly in the realms of redundancy resolution and path planning. This paper introduces a novel approach to simultaneously address these challenges through the concept of Augmented Feasibility Maps, by integrating task coordinates as decision variables into the traditional feasibility maps. We validate the AFM concept by using Rapidly-Exploring Random Trees to explore the maps, demonstrating its efficacy in simulations of various dimensionalities. The method is capable of incorporating kinematic constraints, such as obstacle avoidance while adhering to joint limits. 2025-07-11T10:08:51Z