Ramón Galán

Fuzzy controllers: lifting the linear-nonlinear frontier

Abstract This paper brings back some ideas related with the linear analysis of fuzzy controllers. A fuzzy control algorithm does not go further than a non-linear function described by its inference map. Firstly, it is possible to obtain the inference map corresponding to a classical PID controller by choosing adequately the linguistic terms, the membership functions and the table of rules. Then the inverse problem is presented: to obtain the closer PID to a given fuzzy controller. From these ideas, the paper focuses its attention on the obtainment of a useful tool to design fuzzy controllers at least as good as the PID that allows the system to follow a specified behaviour. The next step is to improve the fuzzy controller parameters. Finally, an industrial application of these ideas is shown. The design of a fuzzy controller over a clinker cooler with grill, improving P and PI controllers already functioning, is discussed.

An optimal fuzzy control system in a network environment based on simulated annealing. An application to a drilling process

This paper shows a strategy for the optimal tuning of a fuzzy controller in a networked control system using an offline simulated annealing approach. The optimal tuning of the fuzzy controller using a maximum known delay is based on the integral time absolute error (ITAE) performance index. The goal is to obtain the optimal tuning parameters for the input scaling factors where the ITAE performance index is minimized. In this study, a step change in the force reference signal is considered a disturbance, and the goal is to assess how well the system follows set-point changes using the ITAE criterion. In order to improve the efficiency of high-performance drilling processes while preserving tool life, the current study focuses on the design and implementation of an optimal fuzzy-control system for drilling force. Simulation results demonstrate good convergence properties of the proposed strategy. Experimental tests of the drilling of two materials (GGG40 and 17-4 PH) corroborate the excellent transient response and the minimum overshoot predicted by the simulation results. Thus, the optimal fuzzy control system reduces the influence of the increase in cutting force that occurs at larger drill depths, eliminating the risk of rapid drill wear and catastrophic drill breakage.

The fuzzy Kalman filter: State estimation using possibilistic techniques

A new method to implement fuzzy Kalman filters is introduced. The combination of possibilistic techniques and the extended Kalman filter has special application in fields where inaccurate information is involved. The novelty of this article comes from the fact that by using possibility distributions, instead of Gaussian distributions, a fuzzy description of the expected state and observation is sufficient to obtain a good estimation. Some characteristics of this approach are that uncertainty does not need to be symmetric, and that a wide region of possible values for the expectations is allowed. To implement the algorithm, this approach also contributes a method to propagate uncertainty through the process model and the observation model, based on trapezoidal possibility distributions. Finally, several examples of a real mobile robot moving through a localization process, while using qualitative landmarks, are shown.

Building geometric feature based maps for indoor service robots

Abstract This paper presents an efficient geometric approach to the Simultaneous Localization and Mapping problem based on an Extended Kalman Filter. The map representation and building process is formulated, fully implemented and successfully experimented in different indoor environments with different robots. The use of orthogonal shape constraints is proposed to deal with the inconsistency of the estimation. Built maps are successfully used for the navigation of two different service robots: an interactive tour guide robot, and an assistive walking aid for the frail elderly.

Consistency improvement for SLAM - EKF for indoor environments

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

Fast exact feature based data correspondence search with an efficient bit-parallel MCP solver

The problem of finding the optimal correspondence between two sets of geometric entities or features is known to be NP-hard in the worst case. This problem appears in many real scenarios such as fingerprint comparisons, image matching and global localization of mobile robots. The inherent complexity of the problem can be avoided by suboptimal solutions, but these could fail with high noise or corrupted data. The correspondence problem has an interesting equivalent formulation in finding a maximum clique in an association graph. We have developed a novel algorithm to solve the correspondence problem between two sets of features based on an efficient solution to the Maximum Clique Problem using bit parallelism. It outperforms an equivalent non bit parallel algorithm in a number of experiments with simulated and real data from two different correspondence problems. This article validates for the first time, to the best of our knowledge, that bit parallel optimization techniques can greatly reduce computational cost, thus making feasible the use of an exact solution in real correspondence search problems despite their inherent NP computational complexity.

Ten Years of Cybertech: The Educational Benefits of Bullfighting Robotics

After 10 years of organizing the Cybertech robotics competition, this paper presents this unique and innovative educational experience of teaching engineering at Universidad Politécnica de Madrid (UPM), Spain. Cybertech is not only a well-known robotic contest in Spain due to the Robotaurus bullfighting, but is also a whole academic activity spanning theory, laboratory practical lessons, seminars, tutoring, and a spectacular contest in which robots, developed by the students, compete. It is an open activity, for all students and grades, requiring knowledge of various subjects such as mechanics, microcontrollers, control, and electronics. The experience acquired has shown how this novel educational approach can boost the motivation of students, who in a real applied project effectively learn not only the particular subject matter, but also skills in teamwork, oral presentations, budget management, and so on. This is considered the flagship of innovation in education at UPM. This paper describes the evolution of Cybertech over the past 10 years, summarizes the educational experience, and provides some statistics and results as well as a perspective for future editions of the competition.

Urbano, an Interactive Mobile Tour-Guide Robot

Autonomous service robot applications can be divided in two main groups: outdoor and field robots, and indoor robots. Autonomous lawnmowers, de-mining and search and rescue robots, mars rovers, automated cargo, unmanned aerial and underwater vehicles, are some applications of field robotics. The term indoor robotics usually applies to autonomous mobile robots that move in a typical populated indoor environment. Robotic vacuum cleaners, entertainment and companion robots or security and surveillance applications are also some examples of successful indoor robot applications. Probably, one of the first real world applications of indoor service robots has been that of mobile robots serving as tour guides in museums or exhibitions. Such one is an extremely interesting application for researchers because allows them to advance in knowledge fields as autonomous navigation in dynamic environments, human robot interaction, indoor environment modelling with simultaneous localization and map building, etc., while also serving as a showcase for attracting the general public as well as possible investors. We have developed our own interactive mobile robot called Urbano, especially designed to be a tour guide in exhibitions. This chapter describes the Urbano robot system, its hardware, software and the experiences we have obtained through its development and use until its actual mature stage. This chapter doesn’t pretend to be an exhaustive technical description of algorithms, mathematical or implementation details, but just an overview of the system. The interested reader will be referred to more specific bibliography for these details. The rest of the chapter is structured as follows: This section presents the related work, other existing systems, as well as our motivation to develop our own robot. Section 2 presents an overview of Urbano, the description of its hardware and also the software components in which the robot control is structured. These components are afterwards described in subsequent sections: Section 3 describes the feature based mapping and navigation subsystem, while the interaction capabilities including our own proprietary voice recognition and synthesis engine will be described in section 4. Section 5 briefly describes the web based remote visit that Urbano is also able to perform. The integration of all these components is managed through a programmable kernel that allows a high level management of all modules, described in section 6. The chapter ends with the presentation of some successful real deployments of Urbano in section 7, and our conclusions in section 8.

Efficient Search Using Bitboard Models

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

Local map fusion for real-time indoor simultaneous localization and mapping

Among the solutions to the simultaneous localization and mapping (SLAM) problem with probabilistic techniques, the extended Kalman filter (EKF) is a very common approach. There are several approaches to deal with its computational cost, usually based on an adequate selection of features to be updated in real time, while the whole map update is delayed or processed in a background task, allowing one to map larger environments or to carry out multirobot experiments. Although these solutions are theoretically sound, there is a great lack of real experiments in large indoor environments due to several previously unknown problems derived from the geometric model of the map features and the inconsistency of the SLAM-EKF algorithm. For the first time, these problems are described and solved, and the implementation of the algorithms and solutions presented in this paper achieve excellent results in experiments in different real large indoor environments.