Félix Monasterio-Huelin

A Fuzzy logic controller with learning through the evolution of its knowledge base

Abstract Fuzzy logic controllers (FLCs) consitute knowledge-based systems that include fuzzy rules and fuzzy membership functions to incorporate human knowledge into their knowledge base. The specification of fuzzy rules and fuzzy membership functions is one of the key question when designing FLCs, and is generally affected by subjective decisions. Some efforts have been made to obtain an improvement on system performance by incorporating learning mechanisms to modify the rules and/or membership functions of the FLC. Genetic algorithms are probabilistic search and optimization procedures based on natural genetics. This paper proposes a way to apply (with a learning purpose) genetic algorithms to FLCs, and presents an application designed to control the synthesis of the biped walk of a simulated 2-D biped robot.

Open E-puck Range & Bearing miniaturized board for local communication in swarm robotics

We have designed and built a new open hardware/ software board that lets miniaturized robots communicate and at the same time obtain the range and bearing of the source of emission. The open E-puck Range & Bearing board improves an existing infrared relative localization/communication software library (libIrcom) developed for the e-puck robot and based on its on-board infrared sensors. The board allows the robots to have an embodied, decentralized and scalable communication system. Its use and capabilities are demonstrated via an alignment experiment.

An Open Localization and Local Communication Embodied Sensor.

In this paper we describe a localization and local communication system which allows situated agents to communicate locally, obtaining at the same time both the range and the bearing of the emitter without the need of any centralized control or any external reference. The system relies on infrared communications with frequency modulation and is composed of two interconnected modules for data and power measurement. Thanks to the open hardware license under which it is released, the research community can easily replicate the system at a low cost and/or adapt it for applications in sensor networks and in robotics.

Collective decision-making based on social odometry

In this paper, we propose a swarm intelligence localization strategy in which robots have to locate different resource areas in a bounded arena and forage between them. The robots have no knowledge of the arena dimensions and of the number of resource areas. The strategy is based on peer-to-peer local communication without the need for any central unit. Social Odometry leads to a self-organized path selection. We show how collective decisions lead the robots to choose the closest resource site from a central place. Results are presented with simulated and real robots.

Zappa, a Quasi-Passive Biped Walking Robot With a Tail: Modeling, Behavior, and Kinematic Estimation Using Accelerometers

In this paper, we describe a biped mechanism model, as well as the biped robot Zappa based on it, that is able to walk using only one actuator that moves its tail. The model has 13 joints and 3 parallel link mechanisms that reduce the passive degrees of freedom to three. We present the behavior of this system when we vary the main parameters that define its gait, and the tail follows a chirp function. It represents an initial methodology for selecting an appropriate set of robot parameters. On the other hand, we present the biped robot Zappa and how we can estimate the kinematics during walking by means of using only three-axis accelerometers. This information allows the attainment of real phase diagrams and, in a future work, the estimation of the zero moment point from the positions and accelerations of the links of the robot.

Heterogeneous collaborative sensor network for electrical management of an automated house with PV energy.

In this paper we present a heterogeneous collaborative sensor network for electrical management in the residential sector. Improving demand-side management is very important in distributed energy generation applications. Sensing and control are the foundations of the “Smart Grid” which is the future of large-scale energy management. The system presented in this paper has been developed on a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead-acid batteries, controllable appliances and smart metering. Therefore, there is a large number of energy variables to be monitored that allow us to precisely manage the energy performance of the house by means of collaborative sensors. The experimental results, performed on a real house, demonstrate the feasibility of the proposed collaborative system to reduce the consumption of electrical power and to increase energy efficiency.

An Approach to Flocking of Robots Using Minimal Local Sensing and Common Orientation

A new algorithm for the control of robot flocking is presented. Flocks of mobile robots are created by the use of local control rules in a fully distributed way, using just local information from simple infra-red sensors and global heading information on each robot. Experiments were done to test the algorithm, yielding results in which robots behaved as expected, moving at a reasonable velocity and in a cohesive way. Up to seven robots were used in real experiments and up to fifty in simulation.

Stability and Smoothness Improvements for an Underactuated Biped with a Tail

In this work we present an important improvement in our model of biped mechanism that allows the elevation in a stable form of the systems feet during the execution of trajectories. This improvement allows for simpler trajectory planning and also facilitates the reduction of losses in the collision between the feet and the ground. On the other hand, we add to the design phase the study of the displacement of the Zero Moment Point, as well as the variation of the normal component of the ground reaction force during the motion of the system. Consideration of the above mentioned magnitudes in the design phase allows us to design the necessary support area of the system. These magnitudes will be used as a smoothness criterion of the ground contact to facilitate the selection of robot parameters and trajectories.

Novel kinematic indices for quantifying movement agility and smoothness after cervical Spinal Cord Injury

BACKGROUND After cervical Spinal Cord Injury (SCI), upper limb movements made by patients have a lack of smoothness and a hand velocity profile characterized by a high number of velocity peaks. OBJECTIVE The aim of the present paper is to propose three novel kinematic indices for quantifying movement agility and smoothness, and to analyze their discriminative capability between healthy and pathological people. METHODS 18 people, healthy and two groups of patients with cervical SCI, participated in the study. Kinematic indices in relation to movement agility and smoothness were computed from hand trajectories and velocity profiles during the performance of the ADL of drinking from a glass. RESULTS The proposed indices discriminated between healthy and SCI people. The results are greater in healthy than SCI people. Both smoothness indices detected significant differences between healthy and both SCI groups. Moreover, the Agility index showed capacity for discriminating between both patients groups. CONCLUSIONS The main contribution of this research consists on the proposal of kinematic indices from experimental data, whose results are dimensionless and relative to a pattern of healthy subjects. We hope that kinematic indices proposed are a step toward the standardization of the quantitative assessment of movement characteristics and functional impairments.

Novel kinematic indices for quantifying upper limb ability and dexterity after cervical spinal cord injury

Loss of motor function is a consequence after cervical spinal cord injury. Three-dimensional kinematic analysis equipments are used for quantifying human movements in clinical laboratories. These systems may provide objectivity to the patient assessments. Nowadays, the kinematic variables found in the literature have some deficiencies, and the efficient management of these data sets is a demand and a challenge in the clinical setting. The aim of the present paper is to propose a set of novel kinematic indices, as a combination of kinematic variables, for quantifying upper limb motor disorders in terms of characteristics in relation to ability and dexterity such as accuracy, efficiency, and coordination. These indices are defined for measuring patients’ motor performance during the activity of daily living of drinking from a glass. This task is included within the upper limb rehabilitative process that patients receive. The main contribution of this research, with the aim of detecting upper limb impairments in patients, consists of the proposal of three kinematic indices from experimental data, whose results are dimensionless and relative to a pattern of healthy subjects. We hope that kinematic indices proposed are a step toward the standardization of the quantitative assessment of movement characteristics and functional impairments.