Ivan Villaverde

• PhD
• Researcher at Tecnalia

This paper introduces an approach to appearance-based mobile robot localization using a new approach to dimensional reduction based on the notion of Lattice Independence called Lattice Independent Component Analysis (LICA). Any algorithm that can select a set of Strong Lattice Independent (SLI) vectors from the data can be applied inside LICA, this...

An innovative neuro-evolutionary approach for mobile robot egomotion estimation with a 3D ToF camera is proposed. The system is composed of two main modules following a preprocessing step. The first module is a Neural Gas network that computes a Vector Quantization of the preprocessed camera 3D point cloud. The second module is an Evolution Strateg...

Many well-known fuzzy associative memory (FAM) models can be viewed as (fuzzy) morphological neural networks (MNNs) because they perform an operation of (fuzzy) mathematical morphology at every node, possibly followed by the application of an activation function. The vast majority of these FAMs represent distributive models given by single-layer ma...

The Linked Multi-Component Robotic Systems (L-MCRS) consists of a group of mobile robots carrying a passive uni-dimensional object (a hose or a wire). It is a recently identified unexplored and unexploited category of multi-robot systems. In this paper we report the first effort on the modeling, control and visual servoing of L-MCRS. Modeling has b...

This paper introduces an approach to appearance based mobile robot localization using Lattice Independent Component Analysis (LICA). The Endmember Induction Heuristic Algorithm (EIHA) is used to select a set of Strong Lattice Independent (SLI) vectors, which can be assumed to be Affine Independent, and therefore candidates to be the endmembers of...

This paper reports an experimental proof-of-concept of a new paradigm in the general field of Multi-Agent Systems, a Linked Multi-component Robotic System. The prototype system realizes a basic task in the general framework of a multi-robot hose transportation system: the trasportation along a linear trajectory. Even this simple task illustrates so...

We propose an evolutionary approach for egomotion estimation with a 3D TOF camera. It is composed of two main modules plus a preprocessing step. The first module computes the Neural Gas (NG) approximation of the preprocessed camera 3D data. The second module is an Evolution Strategy which performs the task of estimating the motion parameters by sea...

Kalman Filters (KF) are at the root of many computational solutions for autonomous systems navigation problems, besides other application domains. The basic linear formulation has been extended in several ways to cope with non-linar dynamic environments. One of the latest trend is to introduce other Computational Intelligence (CI) tools, such as Fu...

Endmembers for the spectral unmixing analysis of hyperspectral images are sets of affinely independent vectors, which define a convex polytope covering the data points that represent the pixel image spectra. Strong lattice independence (SLI) is a property defined in the context of lattice associative memories convergence analysis. Recent results sh...

This paper reports initial steps in the study of control strategies for a multi-robot system trying to move a flexible hose. Our starting point is the hose geometry modeling using cubic splines. The control problem is then stated as the problem of reaching a desired configuration of the spline control points from an initial configuration. The contr...

A neuro-evolutive system for mobile robot ego-motion estimation using time-of-flight (TOF) 3D camera readings is presented in this paper. It is composed of two modules. First, a Neural Gas adaptative algorithm is used to obtain a set of codevectors quantizing the preprocessed 3D measurements provided by the camera. Second, codevector sets from cons...

A Hybrid Intelligent System (HIS) for self-localization working on the readings of innovative 3D cameras is presented in this paper. The system includes a preprocessing step for cleaning the 3D camera readings. The HIS consist of two main modules. First the Self-Organizing Map (SOM) is used to provide models of the preprocessed 3D readings of the c...

Simultaneous Localization and Mapping (SLAM) is a key process in several robotic contexts. In this paper we explore the realization of non-metric SLAM using a visual information based approach relying on the detection of morphologically independent images. Morphologically independent images correspond to approximations to the vertices of the convex...

Strong Lattice Independence implies Affine Independence. Affine Independent sets of vectors define a convex polytope and if this polytope is a good approximation to the convex hull of a set data points, we can use them to represent the data points through their convex coordinates. This representation can be used as a feature extraction or dimension...

Summary. One of the key processes in nowadays intelligent systems is feature extraction. It pervades applications from computer vision to bioinformatics and data mining. The purpose of this chapter is to introduce a new feature extraction process based on the detection of extremal points on the cloud of points that represent the high dimensional da...

Morphologically independent vectors correspond to approximations to the vertices of the convex hull covering the data vectors in high dimensional space. We use Morphological Associative Memories (MAM) for the induction of sets of morphologically independent vectors from data. Simultaneous Localization and Mapping (SLAM) is the process of simultaneo...

Morphological Associative Memories (MAM) have been proposed for image denoising and pattern recognition. We have shown that they can be applied to other domains, like image retrieval and hyperspectral image unsupervised segmentation. In both cases the key idea is that Morphological Autoassociative Memories (MAAM) selective sensitivity to erosive an...

Morphological associative memories (MAM) have been proposed for image denoising and pattern recognition. We have shown that they can be applied to other domains, like image retrieval and hyperspectral image unsupervised segmentation. In both cases the key idea is that morphological auto associative memories (MAAM) selective sensitivity to erosive a...

In this paper we present some real time results of the implementation on a mobile robot of visual self-localization algorithms based on Morphological Heteroassociative Memories (MHM). We propose a dual set of min/max MHM storing the views that serve as landmarks for self localization. The binarized input images are subject to erosion in order to in...