M. Sigut

Ping-pong player prototype

In this paper, a low-cost robot capable of playing ping-pong against human opponent using a vision system to detect the ball is presented. In the subsequent sections, the three main subsystems of the robot, i.e., the vision system, mechanical structure, and the control systems, are described. A prototype has been designed with lightweight and resistant materials to increase the response time and accurateness of the shot. One of the important features of this system is that it uses only one camera to detect the ball, thus reducing the computational time and hardware requirements. To detect the location of the ball, the robot combines the information about the ball and about the shadow it casts on the table. The expert module control defines the game strategy. Orienting the bat in order to return the ball to the desired position on the table does this. In these experiments, the success rate in returning balls was greater than 80%.

Obstacle avoidance for a mobile robot: A neuro-fuzzy approach

In this paper, a neuro-fuzzy approach is presented in order to guide a mobile robot. This task could be carried out specifying a set of fuzzy rules taking into account the different situations found by the mobile robot. This set of fuzzy rules could be optimised according to different criteria. However, the approach shown in this paper, is able to extract a set of fuzzy rules set from a set of trajectories provided by a human. These trajectories guide the mobile robot towards the target in different cases. Thus, it has been possible to obtain the rules and membership functions automatically, whereas other approaches need a previous definition of the rules and membership functions. In order to verify that the obtained behaviour is satisfactory, the neuro-fuzzy approach has been implemented in two mobile robots.

Applying an Ant Colony Optimization Algorithm to an Artificial Vision Problem in a Robotic Vehicle

In this paper, a problem of artificial vision in a robotic autonomous vehicle consisting of the real time detection and tracking of non-structured roads is addressed by applying an Ant Colony Optimization (ACO) algorithm. The solution adopted tries to find some properties describing the probability that a pixel belongs to the boundaries of the road, and then formalize the road detection problem as an optimization one.

Decoupling of the 10 m GranTeCan telescope's primary mirror dynamics and design of a controller for noise rejection

The goal of the paper is to present a method for the decoupling of a multivariable system and to show how this procedure allows the problem of vibrations rejection to be faced. The system we have worked with represents the dynamic behaviour of the GTCs (Gran Telescopio Canarias) 10 m diameter primary mirror. This telescope will be built in the island of La Palma (Spain). The big size of this mirror has caused its segmentation into 36 hexagonal pieces called segments. The system has 108 inputs and the same number of outputs coupled among them. With the decoupling method we present in this work, the problem of designing a controller for a MIMO system has been converted into the calculus of 108 SISO controllers. One of these controllers is presented as an example of how the decoupling process facilitates the noise rejection.

A predictive control algorithm with interpolation for a robot manipulator with constraints

The paper presents an efficient control algorithm applied on a two-link robot manipulator with input constraints. The algorithm proposes a suboptimal solution to the predictive control problem with infinite prediction horizon, by mean of interpolations between the unconstrained optimal solution and other constrained solutions. The control strategy is based on inserting the predictive controller in an adaptive perturbation scheme. The efficiency of the proposed strategy is shown by simulation.

Disturbances rejection on a robot arm using an efficient predictive controller

Abstract This work proposes a predictive controller with interpolation in order to improve the behaviour of a typical MPC when the system presents constraints. Particularly, it is interesting to see how the interpolation, between the solution of the optimal unconstrained problem and other feasible solutions, assures the stability of the system in presence of disturbances. The system in which the controller is applied is a two-link robot manipulator arm. The predictive controller is inserted in an adaptive perturbation scheme to change adequately the nominal inputs, given by an inverse dynamics controller, in order to reject the disturbances produced. The efficiency of the proposed strategy is shown by simulation.

Towards a Multiagent Approach for the VERDINO Prototype

This paper presents a work in progress about the design and development of a multiagent system for an autonomous vehicle (VERDINO). This vehicle (a standard golf cart) has been provided with many different sensors and actuators. The future multiagent system is intended to manage the data provided by the sensors and act on steering orientation and brake and throttle pedals.

Detection of Non-structured Roads Using Visible and Infrared Images and an Ant Colony Optimization Algorithm

In this paper, the problem of road detection on unstructured environments is mapped as an optimization one, and an Ant Colony Optimmization algorithm is applied to solve it. This allows that the artificial agents make up for the lack of edge input information with their common memory. This common memory contains the paths followed by the entire colony. From an intuitive point of view, it can be said that in the areas where no edge information can be obtained, the agents will construct pheromone bridges (to the next edge detected pixels), that will allow them to continue constructing their solution, achieving this way a robust road detection. The input information for the algorithm will consist in images captured by cameras in the visible and in the infrared spectrums. Some features of the roads that are wanted to be detected make that in some cases the information from the visible spectrum is more useful than the information from the infrared spectrum while in other cases the infrared ones are more useful. This is why both sources of data are used to improve the global performance of the proposed method.

An infrared and neuro-fuzzy-based approach for identification and classification of road markings

A low-cost infrared and Neuro-Fuzzy-based approach for identification and classification of road markings is presented in this paper. The main task of the designed prototype, implemented at the University of La Laguna, is to collect information by a set of infrared sensors and to process it in an intelligent mode. As an example, it should inform the driver about the different signs and elements it is driving on, complementing other well-known and widely used security devices. For the identification and classification stages, a Neuro-Fuzzy approach has been chosen; given it is a good option in order to get fuzzy rules and memberships functions in an automatic way.

FOUR ROTOR HELICOPTER CONTROL LABORATORY PLANT

Abstract In this paper, a test-bed for teaching in multivariable system is presented. Firstly, the different aspects of the prototype construction will be described, making a special emphasis in the mechanics, the design of the sensorial and actuation systems and the prototype control. Next, the real time control software will be explained. The mathematical model of the plant is presented in order to design a control strategy, test it in simulation and validate in the real system.