Enrique Santiso

Wheelchair for physically disabled people with voice, ultrasonic and infrared sensor control

This paper describes a wheelchair for physically disabled people developed within the UMIDAM Project. A dependent-user recognition voice system and ultrasonic and infrared sensor systems has been integrated in this wheelchair. In this way we have obtained a wheelchair which can be driven with using voice commands and with the possibility of avoiding obstacles and downstairs or hole detection. The wheelchair has also been developed to allow autonomous driving (for example, following walls). The project, in which two prototypes have been produced, has been carried out totally in the Electronics Department of the University of Alcalá (Spain). It has been financed by the ONCE. Electronic system configuration, a sensor system, a mechanical model, control (low level control, control by voice commands), voice recognition and autonomous control are considered. The results of the experiments carried out on the two prototypes are also given.

Electronic control of a wheelchair guided by voice commands

Abstract This paper describes the control of an electric wheel chair with voice commands. This chair has been developed and built at the U.A.H. Electronic Department and financed by the ONCE Foundation (Spain). The first prototype consists of voice recognition, motor control, user interface and central processor modules. The electronic system allows the chair user a safe, easy ride, and guarantees the concordance between user commands and actual trajectories. Furthermore, the system has been designed to allow the addition of future features, like obstacle and stair detection and the tele-commanding of electrical household appliances from the chair.

Guidance of a mobile robot using an array of static cameras located in the environment

Abstract This paper presents a new proposal for positioning and guiding mobile robots in indoor environments. The proposal is based on the information provided by static cameras located in the movement environment. This proposal falls within the scope of what are known as intelligent environments; in this case, the environment is provided with cameras that, once calibrated, allow the position of the robots to be obtained. Based on this information, control orders for the robots can be generated using a radio frequency link. In order to facilitate identification of the robots, even under extremely adverse ambient lighting conditions, a beacon consisting of four circular elements constructed from infrared diodes is mounted on board the robots. In order to identify the beacon, an edge detection process is carried out. This is followed by a process that, based on the algebraic distance, obtains the estimated ellipses associated with each element of the beacon. Once the beacon has been identified, the coordinates of the centroids for the elements that make up the beacon are obtained on the various image planes. Based on these coordinates, an algorithm is proposed that takes into account the standard deviation of the error produced in the various cameras in ascertaining the coordinates of the beacon’s elements. An odometric system is also used in guidance that, in conjunction with a Kalman Filter, allows the position of the robot to be estimated during the time intervals required to process the visual information provided by the cameras.

Using PCA in time-of-flight vectors for reflector recognition and 3-D localization

This paper presents a reflector recognition and localization technique in three-dimensional (3-D) environments, using only times-of-flight (TOFs) data obtained from ultrasonic transducers. The recognition and localization technique is based on the principal component analysis applied to the TOF vectors originating from a sensor that contains two emitting transducers and several receivers. The two emitters simultaneously transmit two coded pulses that are detected later on and discriminated by the receivers, after being reflected in the environment. The proposed technique allows for the possibility of not only recognizing the reflectors, but also estimating approximately its localization referred to the sensor. This technique has been tested with three types of reflectors in 3-D environments: planes, edges, and corners. The achieved results are very satisfactory for reflectors located in the range 50-350 cm.

Localization of Mobile Robots Using Odometry and an External Vision Sensor

This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields.

Fuzzy Decentralized Control for guidance of a convoy of robots in non-linear trajectories

This article presents a control solution for the guidance of wheeled convoy units in non-linear trajectories. The proposal consists of a Mamdani fuzzy controller to solve the Decentralized Control problem as applied to a set of units following a leader, whilst guaranteeing the so called “string stability” condition of the convoy.

Teaching equipment for training in the control of DC, brushless, and stepper servomotors

This paper describes teaching equipment for instruction in motor control developed in the Electronics Department of the University of Alcala, Spain. This project (called Project DEDALO) involved the development of complete electronic equipment for studying and carrying out experiments on the control of stepper, medium and low-power DC and brushless motors. The use of a personal computer as user interface (for the setting up of different types of motors and controls, display of the control structures, signal display, generation of commands, etc.) makes the equipment very easy to use and highly versatile.

Method to measure the rotation angles in vibrating systems

In the measurement systems of three-dimensional (3-D) positions using active vision (e.g., laser and camera), it is necessary to know the precise rotation angles of the camera and the laser with respect to the object on which the 3-D coordinate measures are desired. A small variation of these angles can result in substantial errors of measurement. In this work, we present a novel solution to measure the rotation-angle variations of the elements that form the measurement system under vibration. In our case, the objective is to determine these angles for a 3-D-coordinate measurement system of the wires that feed the electric trains (contact wires). The measurement system must go onboard a measurement car. The 3-D-coordinate measurements are done by triangulation, from a digital camera and a laser that emits a plane of structured light incident on contact wires. In order to measure the angle variations, which result from the vibrations that take place in the measurement system, two line scan cameras and two artificial marks are used. In this paper, the procedure that allows the measurement of the rotation angles of the camera and the laser, the proposed models, and the results obtained in the simulations are shown.

Localization and Geometric Reconstruction of Mobile Robots Using a Camera Ring

In this paper, a system capable of obtaining the 3-D pose of a mobile robot using a ring of calibrated cameras attached to the environment is proposed. The system robustly tracks point fiducials in the image plane of the set of cameras generated by the robots rigid shape in motion. Each fiducial is identified with a point belonging to a sparse 3-D geometrical model of the robots structure. Such a model allows direct pose estimation from image measurements, and it can easily be enriched at each iteration with new points as the robot motion evolves. The process is divided into an initialization step, where the structure of the robot is obtained, and an online step, which is solved using sequential Bayesian inference. The approach allows the proper modeling of uncertainty in measurements and estimations, and at the same time, it serves as a regularization step in pose estimation. The proposed system is verified using simulated and real data.

Alternative Sensor System and MLP Neural Network for Vehicle Pedal Activity Estimation

It is accepted that the activity of the vehicle pedals (i.e., throttle, brake, clutch) reflects the driver’s behavior, which is at least partially related to the fuel consumption and vehicle pollutant emissions. This paper presents a solution to estimate the driver activity regardless of the type, model, and year of fabrication of the vehicle. The solution is based on an alternative sensor system (regime engine, vehicle speed, frontal inclination and linear acceleration) that reflects the activity of the pedals in an indirect way, to estimate that activity by means of a multilayer perceptron neural network with a single hidden layer.