Indoor mobile robots navigation must use external sensors to complement odometry. This paper analyses two different external sensors such as a laser LMS-200 and an omnidirectional camera Mobotix C2S. Experiments with only one of these sensors and with both integrated are carried out on a tour guide robot in order to obtain conclusions about their contribution to robot pose estimation, and how to locate external landmarks in the environment.

Thanks to the numerous attempts that are being made to develop autonomous robots, increasingly intelligent and cognitive skills are allowed. This paper proposes an automatic presentation generator for a robot guide, which is considered one more cognitive skill. The presentations are made up of groups of paragraphs. The selection of the best paragraphs is based on a semantic understanding of the characteristics of the paragraphs, on the restrictions defined for the presentation and by the quality criteria appropriate for a public presentation. This work is part of the ROBONAUTA project of the Intelligent Control Research Group at the Universidad Politécnica de Madrid to create "awareness" in a robot guide. The software developed in the project has been verified on the tour-guide robot Urbano. The most important aspect of this proposal is that the design uses learning as the means to optimize the quality of the presentations. To achieve this goal, the system has to perform the optimized decision making, in different phases. The modeling of the quality index of the presentation is made using fuzzy logic and it represents the beliefs of the robot about what is good, bad, or indifferent about a presentation. This fuzzy system is used to select the most appropriate group of paragraphs for a presentation. The beliefs of the robot continue to evolving in order to coincide with the opinions of the public. It uses a genetic algorithm for the evolution of the rules. With this tool, the tour guide-robot shows the presentation, which satisfies the objectives and restrictions, and automatically it identifies the best paragraphs in order to find the most suitable set of contents for every public profile.

This paper presents the structure and operation principles of an emotional model. It is a dynamic state-space model where state variables represent the emotional state. Model matrices are time variant. A method based on fuzzy inference systems is developed to calculate the matrix coefficients at each time step. The simulation results of the guide robot case study are presented.

It is the authors' belief that the ability of processors to compute bit parallel operations should have a right to exist as an optimization discipline, rather than a state-of- the-art technique. This paper is a step forward in this direction analysing a number of key issues related to bit model design and implementation of search problems. Building efficient search algorithms optimized at bit level is a difficult task It requires not only a good implementation but also an adequate model so as to make bitwise operations meaningful, and only by addressing design and implementation globally an improvement in efficiency can be obtained. On the other hand, we have proved in this paper that the improvement can conceivably be exponential on the size of the CPU register for problems in NP. This global approach has been used to implement the fastest complete algorithm, to the best of our knowledge, for the maximum clique problem, an important NP-hard combinatorial problem from the graph domain. Our solver clearly outperforms other existing algorithms for hard instances, in some cases by nearly an order of magnitude.

The solution to the simultaneous localization and mapping (SLAM) problem using an extended Kalman filter (EKF) is the most extended despite the inconsistency of its estimation, a problem that has been largely avoided in the literature. We review current existing approaches and present novel solutions to this problem that let us to build large monolithic feature based maps of indoor environments

This paper shows a way to speed up search by using an encoding at bit level to model a particular domain. A bitboard is an unsigned integer whose bits have been given an interpretation in the world of discourse. In models encoded in such a way, states will be described internally as a set of bitboard tuples, whilst operators which allow for transitions between states are essentially bitwise operations over elements belonging to that set. Given a 64-bit processor word, for each transition it would be theoretically possible to reach another state 64 times faster than with a normal encoding, fast transitions being one of the main issues for efficient search algorithms. We have analysed some other key issues related to efficient bitboard model design and formalised the concepts of well formed heuristics and bitboard guides. We have used this approach to solve instances of the maximum clique problem thus increasing the performance of one of the fastest algorithms known in the domain for optimal search

Guido is a healthcare robot that serves as support and navigation aid for the frail and visually impaired. The previous assistive navigation software has been replaced by a full map based control, including real time feature based map building (SLAM) and pose tracking (both using an EKF), and path planning and collision avoidance. Real experiments have been carried out, both in the lab and in the hospital, with great success, showing a high improvement in the ease of use and convenience of the system. The map building and editing tools have proved to be extremely useful, enabling the system to be installed in a new environment in just minutes.

Presents the first approach towards the main goal of developing a completely autonomous robot that serves as a local and remote guide at a trade fair. Innovative solutions are provided to solve several problems found in this environment. Reactive-perceptual behaviors are executed to provide motion while a low level controller avoids collisions. A virtual corridor map, simulated perception, and an extended Kalman filter for localization, are used to overcome the lack of perception. Voice synthesizing is proved to be an effective aid for navigation, as well as for the overall success and acceptance of the system. A Denning Mrv4 robot called Blacky was used to carry out experiments in actual environments on three occasions, and the obtained conclusions sound promising for future research.