Sergio Cebollada

Sergio Cebollada
Universidad Miguel Hernández de Elche | UMH · Department of Systems and Automatic Engineering

Master of Engineering

About

29
Publications
3,849
Reads
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123
Citations
Citations since 2017
29 Research Items
123 Citations
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20172018201920202021202220230102030405060
20172018201920202021202220230102030405060
Introduction
Currently, I am studying AI techniques to develop robust visual localization methods based on omnidirectional images.

Publications

Publications (29)
Article
Full-text available
The aim of this paper is to achieve the optimal hyperparameters setup of a convolutional neural network (CNN) to address the localization of a mobile robot. The localization problem is solved with a hierarchical approach by using omnidirectional images as provided by a catadioptric visual sensor, with no panoramic conversion. In this way, we propos...
Article
Full-text available
This paper reports and evaluates the adaption and re-training of a Convolutional Neural Network (CNN) with the aim of tackling the visual localization of a mobile robot by means of a hierarchical approach. The proposed method addresses the localization problem from the information captured by a catadioptric vision sensor mounted on the mobile robot...
Conference Paper
En este artículo se presenta un estudio de alineamiento 3D de diferentes posiciones de un robot en entornos de interior. El alineamiento que se desea resolver se desenvuelve en escenarios de difícil caracterización. Para resolver este problema se plantea utilizar información RGB-D, esto es, información visual y de profundidad obtenida del entorno a...
Chapter
This paper presents a method to solve the forward kinematic problem of parallel robots, obtaining all real solutions. The method is illustrated with the 3UPS-PU parallel robot, and consists in eliminating one unknown to obtain an equation that constrains the admissible values of the remaining unknowns. This constraint defines a curve in the plane o...
Chapter
In this work, some holistic description methods are evaluated in the framework of a localization task in heterogeneous zones, task that an autonomous robot should be able to perform correctly. The unique source of information is an omnidirectional vision sensor and the work is focused on the use of holistic or global-appearance techniques to descri...
Chapter
The present work introduces a study about the use of a deep learning tool to tackle the visual localization. The approach proposed consists in developing a Convolutional Neural Network (CNN) with the aim of addressing the room retrieval task. Additionally, the network can be used to extract holistic descriptors from intermediate layers. Therefore,...
Chapter
El objetivo del presente trabajo es abordar la localización de un robot móvil mediante el entrenamiento de una Red Neuronal Convolucional (CNN) de manera que se obtengan unos resultados óptimos. El problema de localización se aborda de forma jerárquica empleando un sistema catadióptrico omnidireccional y se trabaja directamente con las imágenes cap...
Article
Full-text available
Understanding the environment is an essential ability for robots to be autonomous. In this sense, Convolutional Neural Networks (CNNs) can provide holistic descriptors of a scene. These descriptors have proved to be robust in dynamic environments. The aim of this paper is to perform hierarchical localization of a mobile robot in an indoor environme...
Article
Nowadays, the field of mobile robotics has experienced an important evolution and these robots are more commonly proposed to solve different tasks autonomously. The use of visual sensors has played an important role in mobile robotics tasks during the past few years due to the advances in computer vision hardware and algorithms. It is worth remarki...
Article
Full-text available
In this work, an incremental clustering approach to obtain compact hierarchical models of an environment is developed and evaluated. This process is performed using an omnidirectional vision sensor as the only source of information. The method is structured in two loop closure levels. First, the Node Level Loop Closure process selects the candidate...
Article
Full-text available
This paper is focused on the design of a mobile robot whose objective is to apply thermal insulation spray in underfloor voids, to improve the energy efficiency of buildings. Solving robustly the mapping and localization problems is crucial to achieve a high degree of autonomy during the development of this task. Nevertheless, underfloor voids cons...
Chapter
Autonomous robots should be able to perform localization and map creation robustly. In order to solve these problems many studies and techniques have been evaluated over the past few years. This work focuses on the use of an omnidirectional vision sensor and global appearance techniques to describe each image. Global-appearance techniques consist i...
Article
Full-text available
This paper presents an extended study about the compression of topological models of indoor environments. The performance of two clustering methods is tested in order to know their utility both to build a model of the environment and to solve the localization task. Omnidirectional images are used to create the compact model, as well as to estimate...
Article
Full-text available
In this paper, a hierarchical localization framework within indoor environments is proposed and evaluated, considering severe variations of the illumination conditions. The only source of information both to build a model of the environment and to solve the localization problem is a catadioptric vision system, which is mounted on the mobile robot....
Article
This paper presents a novel robotic system that applies spray foam insulation in underfloor voids in order to improve the energy efficiency of buildings. The work focuses on solving the mapping and localization problems in such environments, since they are a key factor in the autonomy of the robot. Solving these tasks in underfloor voids is especia...

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