Robotic wheelchair controlled through a vision-based interface

In this work, a vision-based control interface for commanding a robotic wheelchair is presented. The interface estimates the orientation angles of the user's head and it translates these parameters in command of maneuvers for different devices. The performance of the proposed interface is evaluated both in static experiments as well as when it is applied in commanding the robotic wheelchair. The interface calculates the orientation angles and it translates the parameters as the reference inputs to the robotic wheelchair. Control architecture based on the dynamic model of the wheelchair is implemented in order to achieve safety navigation. Experimental results of the interface performance and the wheelchair navigation are presented.Fil: Perez, Elisa. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; ArgentinaFil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Nasisi, Oscar Herminio. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Bastos, Teodiano Freire. Universidade Federal do Espírito Santo; BrasilFil: Mut, Vicente Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentin

A mosaic of eyes

Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties

Bio-signal based control in assistive robots: a survey

Recently, bio-signal based control has been gradually deployed in biomedical devices and assistive robots for improving the quality of life of disabled and elderly people, among which electromyography (EMG) and electroencephalography (EEG) bio-signals are being used widely. This paper reviews the deployment of these bio-signals in the state of art of control systems. The main aim of this paper is to describe the techniques used for (i) collecting EMG and EEG signals and diving these signals into segments (data acquisition and data segmentation stage), (ii) dividing the important data and removing redundant data from the EMG and EEG segments (feature extraction stage), and (iii) identifying categories from the relevant data obtained in the previous stage (classification stage). Furthermore, this paper presents a summary of applications controlled through these two bio-signals and some research challenges in the creation of these control systems. Finally, a brief conclusion is summarized

ROS-Based Indoor Autonomous Exploration and Navigation Wheelchair

The aim of this project is to create a platform that when implemented to an electric wheelchair could give to the users different control methods to suit their needs. It will be composed of a adaptive control system by means of different controllers and an autonomous control system. In addition, a system for measuring physiological parameters has been implemented to supervise the user?s health state when it is used sites such as hospitals, and their emotional state in order to optimize their period of adaptation to the control. It is oriented to offering people with severe disabilities, who cannot control a wheelchair by themselves, independent mobility from their caregivers in indoor spaces. The control platform has the objective to be as economic as possible and adaptable to any electric wheelchair model.El objetivo de este proyecto es crear una plataforma que, una vez implementada en una silla de ruedas eléctrica, pueda proporcionar a los usuarios diferentes métodos de control que se adapten a sus necesidades. Ésta estará compuesta por un sistema de control adaptativo, mediante diferentes controladores, y un sistema de control autónomo. Aparte, también se ha implementado un sistema de medida de parámetros fisiológicos que permite supervisar el estado de salud del usuario cuando se utiliza en lugares como hospitales, y el estado emocional para poder optimizar su fase de adaptación al control. Está orientado a ofrecer a las personas con discapacidades graves, que no pueden controlar por sí mismas una silla de ruedas, movilidad independiente de sus cuidadores en espacios interiores. La plataforma tiene el objetivo de ser adaptable a cualquier modelo de silla de ruedas eléctrica y ser lo más económica posible.L'objectiu d'aquest projecte és crear una plataforma que, un cop implementada a una cadira de rodes elèctrica, pugui proporcionar als usuaris diferents mètodes de control que s'adaptin a les seves necessitats. Aquesta estarà composta per un sistema de control adaptatiu, mitjançant diferents controladors, i un sistema de control autònom. A part, també s'ha implementat un sistema de mesura de paràmetres fisiològics que permet supervisar l'estat de salut de l'usuari quan es fa servir en llocs com hospitals, i l'estat emocional per tal de poder optimitzar la seva fase d'adaptació al control. Està orientat a oferir a les persones amb discapacitats greus, que no poden controlar per elles mateixes una cadira de rodes, mobilitat independent dels seus cuidadors en espais interiors. La plataforma té l'objectiu de ser adaptable a qualsevol model de cadira de rodes elèctrica i ser el més econòmica possible

CES-513 Stages for Developing Control Systems using EMG and EEG Signals: A survey

Bio-signals such as EMG (Electromyography), EEG (Electroencephalography), EOG (Electrooculogram), ECG (Electrocardiogram) have been deployed recently to develop control systems for improving the quality of life of disabled and elderly people. This technical report aims to review the current deployment of these state of the art control systems and explain some challenge issues. In particular, the stages for developing EMG and EEG based control systems are categorized, namely data acquisition, data segmentation, feature extraction, classification, and controller. Some related Bio-control applications are outlined. Finally a brief conclusion is summarized.

INTELLIGENT VISION-BASED NAVIGATION SYSTEM

This thesis presents a complete vision-based navigation system that can plan and follow an obstacle-avoiding path to a desired destination on the basis of an internal map updated with information gathered from its visual sensor. For vision-based self-localization, the system uses new floor-edges-specific filters for detecting floor edges and their pose, a new algorithm for determining the orientation of the robot, and a new procedure for selecting the initial positions in the self-localization procedure. Self-localization is based on matching visually detected features with those stored in a prior map. For planning, the system demonstrates for the first time a real-world application of the neural-resistive grid method to robot navigation. The neural-resistive grid is modified with a new connectivity scheme that allows the representation of the collision-free space of a robot with finite dimensions via divergent connections between the spatial memory layer and the neuro-resistive grid layer. A new control system is proposed. It uses a Smith Predictor architecture that has been modified for navigation applications and for intermittent delayed feedback typical of artificial vision. A receding horizon control strategy is implemented using Normalised Radial Basis Function nets as path encoders, to ensure continuous motion during the delay between measurements. The system is tested in a simplified environment where an obstacle placed anywhere is detected visually and is integrated in the path planning process. The results show the validity of the control concept and the crucial importance of a robust vision-based self-localization process

Modeling and Fabrication of Smart Robotic Wheelchair Instructed by Head Gesture

The confronting problem faced by the handicapped, paralyzed, disabled, and quadriplegic people is their independent mobility. They need external assistance to perform their daily life activities. This paper aims to solve that problem by smart designing and deployment of the robotic wheelchair for those who cannot perform their voluntary activities and movements. The proposed automated wheelchair comprises two parts; the first part is the user's helmet that works as a master device, and the second part is a slave device, a smart wheelchair. The master device consists of an accelerometer, microcontroller, and wireless transmitter, in which the Accelerometer recognizes the movements of the user's head and transmits the signal according to the tiltation of the user's head. Besides this, the slave device consists of a wireless receiver, microcontroller, Gyroscope, power MOSFETs, and DC geared motors mounted on a smart wheelchair, which response as per the instructions of the master device. Furthermore, the paper also provides a brief construction of this mechatronic and amphibian system using static and dynamic equations