Instrumentação de cadeira de rodas motorizada para usuários com tetraplegia

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Faculdade UnB Gama (FGA), Engenharia Eletrônica, 2018.A tecnologia está sendo cada vez mais aplicada na melhoria da qualidade de vida das pessoas. Um dos ramos que tem sido bastante desenvolvido é o da robótica móvel. Pensando nas possibilidades que ela pode oferecer à qualidade de vida das pessoas que dependem de cadeira de rodas, o presente trabalho apresenta uma proposta de instrumentação de uma cadeira de rodas manual já motorizada, utilizando elementos da robótica móvel para projetar uma cadeira na qual os usuários com tetraplegia possam futuramente usufruir de uma maior liberdade de locomoção. O projeto de instrumentação têm por objetivos determinar a distância que a cadeira está de obstáculos e detectar desníveis na frente e atrás da cadeira. Para isso, foram instalados sensores de ultrassom e infravermelhos em um Arduino Mega ADK que irá ler os dados dos sensores e processar as informações aplicando o Filtro de Kalman e realizando a fusão sensorial, quando necessário. Com o auxílio de uma impressora 3D e outros materiais recicláveis, projetou-se suportes para comportar os sensores nos locais mais adequados da cadeira. Os resultados obtidos apresentam as vantagens e desvantagens de utilizar os sensores selecionados, além de permitir uma análise sobre a estrutura utilizada para fixar os sensores na cadeira de rodas manual.Technology has been increasingly applied in order to improve quality of life of people. One of the main areas that has been developed is mobile robotics. ThinkingThinking on the possibilities that it could do improve quality of life of people who depend on the use of wheelchairs, this work presents a proposal of instrumentation of a motorized wheelchair, using elements of mobile robotics to design a wheelchair that enables quadriplegic users to enjoy more freedom of locomotion.The instrumentation project goals include determining the distance between the wheelchair and its obstacles as well as detecting gaps located at its frontal and rear parts. In order to do that, ultrasound and infrared sensors were installed on an Arduino Mega ADK, which reads the sensor data and processes its information applying a Kalman Filter, as well as sensor fusion when necessary. Using a 3D printer and other recyclable materials, supports for the sensors were designed to place sensors at the most adequate locations of the wheelchair The results obtained present the advantages and disadvantages of using the selected sensors. Also, they allow an analysis about the structure used to set the sensors on a manual wheelchair

Gaze-tracking-based interface for robotic chair guidance

This research focuses on finding solutions to enhance the quality of life for wheelchair users, specifically by applying a gaze-tracking-based interface for the guidance of a robotized wheelchair. For this purpose, the interface was applied in two different approaches for the wheelchair control system. The first one was an assisted control in which the user was continuously involved in controlling the movement of the wheelchair in the environment and the inclination of the different parts of the seat through the user’s gaze and eye blinks obtained with the interface. The second approach was to take the first steps to apply the device to an autonomous wheelchair control in which the wheelchair moves autonomously avoiding collisions towards the position defined by the user. To this end, the basis for obtaining the gaze position relative to the wheelchair and the object detection was developed in this project to be able to calculate in the future the optimal route to which the wheelchair should move. In addition, the integration of a robotic arm in the wheelchair to manipulate different objects was also considered, obtaining in this work the object of interest indicated by the user's gaze within the detected objects so that in the future the robotic arm could select and pick up the object the user wants to manipulate. In addition to the two approaches, an attempt was also made to estimate the user's gaze without the software interface. For this purpose, the gaze is obtained from pupil detection libraries, a calibration and a mathematical model that relates pupil positions to gaze. The results of the implementations have been analysed in this work, including some limitations encountered. Nevertheless, future improvements are proposed, with the aim of increasing the independence of wheelchair user