http://www.iri.upc.edu
The Institut de Robòtica i Informàtica Industrial is a joint research Institute of the Spanish Council of Scientific Research (CSIC) and the Technical University of Catalonia (UPC). It is a multidisciplinary center where CSIC and UPC researchers carry out basic and pre-industrial technological research on robotics and applied informatics. The research activities at IRI are divided in two Research Departments: Robotics and Automatic Control.

The Robotics Department has fundamental research groups in the areas of Kinematics and Robot Design; Perception and Manipulation; and Mobile Robotics and Intelligent Systems. The Department includes researchers with diverse complementary backgrounds, from theoretical (mathematics, physics) to the various engineering areas (computer science, industrial, automation). This enables us to tackle core robotics problems with grounded scientific rigor, but with realistic application scenarios in mind. The fields of expertise of the Department’s senior members span all areas of robotics research from perception systems (computer vision, Bayesian estimation, pattern recognition, learning) to autonomous navigation (localization, mapping, navigation, path planning), or geometric methods in robotics (position and motion analysis, mechanism design, mechanism synthesis).

The Automatic Control Department develops basic and applied research in automatic control theory, with emphasis on nonlinear control, predictive optimal control, diagnosis and fault‐tolerant control and large‐scale networked systems control, energy based modeling and control, and decision support systems, for applications in water and energy systems.

Research Interests
• KINEMATICS AND ROBOT DESIGN
• PERCEPTION AND MANIPULATION
• MOBILE ROBOTICS AND INTELLIGENT SYSTEMS
• AUTOMATIC CONTROL

Current Projects
MiPRCV ‐ Multimodal interaction in pattern recognition and computer vision.
MIPRCV establishes a five‐years research program to develop pattern recognition and computer vision approaches that explicitly deal with the challenges and opportunities entailed by the human‐interaction paradigm. Based on these approaches, it also aims at implementing actual systems and prototypes for a number of important MI applications. The ultimate goal is to show how existing PR and CV technologies can naturally evolve to help the development of advanced multi‐modal interactive systems that will realize the long standing promises of a seamless synergy between persons and machines.

URUS: Ubiquitous networking robotics in urban settings
The URUS project focuses on the design and development of a cognitive networked robot architecture that in a cooperative way interacts with human beings and the environment for tasks of guidance, assistance, transportation of goods, and surveillance in urban areas. This robot architecture integrates cooperating urban robots, intelligent sensors (video cameras, acoustic sensors, etc.), intelligent devices (PDA, mobile telephones, etc.) and communications. The main scientific and technological challenges addressed in the project are: navigation and motion coordination between robots; cooperative environment perception; cooperative map building and updating; task negotiation within cooperative systems; human‐robot interaction; and wireless communication strategies between users (mobile phones, PDAs), the environment (cameras, acoustic sensors, etc.), and the robots.

UbRob ‐ Ubiquitous robotics for urban areas
This is a National project complementary to the European project URUS. In URUS the focus is on Cooperative Robotics, whereas in this project the focus is to develop new techniques that are not considered in the URUS project, for example the design of planning with SLAM for navigation, the recognition of objects invariant to rotation and illumination or the search of algorithms for calibration of ubiquitous sensors, along with new experiments for assistance and guiding of people in an urban area.

PACO‐PLUS ‐ Perception, action & cognition through learning of object‐action complexes
The project aims at the design of a cognitive robot that is able to develop perceptual, behavioral and cognitive categories in a measurable way and communicate and share these with humans and other artificial agents. To achieve this, the project brings together a consortium of robotics researchers, engineers, computer vision scientists, linguists, theoretical neuroscientists and cognitive psychologists. Central to the approach is the axiomatic assumption that objects and actions are inseparably intertwined and, thus, the so‐called Object‐Action Complexes (OACs) are the building blocks of cognition.

PAU - Perception and Action under Uncertainty
The goal of this project is to provide a theoretical foundation of the relation between perception and action in the presence of uncertainty. The main outcome of the project will be novel scientific contributions on Bayesian estimation applied to robotics problems with large state spaces. In particular, the project will produce: novel uncertainty parameterizations that allow efficient inference, new probabilistic hypotheses testing strategies with respect to information load, new active exploration paradigms for scene and object model acquisition, and novel pose estimation algorithms.

CUIK+ ‐ Analysis and motion planning of complex robotic systems
The goal of this project is to extend the technique for solving the position analysis of robotic systems of arbitrary topology, developed in the aforementioned project, to deal with robotic systems of higher complexity. A system’s complexity depends on two parameters: its cardinality (the number of involved bodies) and its mobility (the dimension of its C‐space). The present algorithm solves efficiently all cases of low mobility and cardinality, and we seek to extend it in order to treat cases of high mobility and/or cardinality, unsolvable until present. The developed techniques find applications to problems like the kinematic analysis and motion planning of deployable structures, parallel robots, articulated hands, and molecular structures, among others.

MANIPTENS ‐ Study and design of a hyper‐actuated mechanical manipulator based on tensegrity structures
In this project we are designing a tensegrity prototype that avoids collisions with an external moving plane and collisions between its elements. Collisions are taken as additional constraints inside the non‐linear optimization process that computes a stable structure when varying the longitude of some of its elements.

DICOPEM ‐ Advances in the modeling and design of controllers for systems based on PEM type fuel cells
This project is focused on the modeling and design of controllers for PEMFC. We are working on obtaining a detailed model of the non‐linear phenomena inside the fuel cell through the Port Hamiltonian System (PHS) formalism, which permits a unified treatment of the multi‐domain system. Because of known limitations about the humidification subsystem modeling and the diffusion modeling, these aspects will be given special attention. The second objective of the project is to obtain reduced models that preserve the PHS structure introducing, for the diffusion effects, fractionary transfer functions. Finally, the third objective of the project is the proposal of controllers. Taking advantage of PHS theory and the modeling results, we want to design non‐linear robust controllers that assure reliable and efficient operation, helps long aging, and provides quality energy able to follow load variations.

ITACA‐ Integration of advanced modeling, control, and control techniques applied to the management of the water cycle
The water cycle refers to systems of recruitment, production, transportation and distribution of drinking water and urban drainage systems, collection of sewage and rainwater that return water to the natural environment, usually, after a cleansing process. This project refers to the use of advanced control techniques to the autonomous management of such systems.

ELISSA ‐ Electric incidence scheduling and supervisory algorithms
The ELISSA project, part of the larger CRISALDA CENIT project, develops new algorithms for intelligent energy routing on large distribution networks. The project seeks to determine through which paths should the energy flow on such networks, in order to avoid line overloads and resource conflicts, minimizing operational costs and blackout risks at the same time. The project will provide tools for safe reconfiguration and after‐blackout recovery of such networks, based on the constraint programming paradigm.