Mestrado em Engenharia Elétrica

URI Permanente para esta coleção

http://repositorio.ufes.br/handle/10/17619

Nível: Mestrado Acadêmico
Ano de início:
Conceito atual na CAPES:
Ato normativo:
Periodicidade de seleção:
Área(s) de concentração:
Url do curso:

Navegar

Navegando Mestrado em Engenharia Elétrica por Autor "Alsina, Pablo Javier"

Agora exibindo 1 - 2 de 2
  • Nenhuma Miniatura disponível
    Item
    Design and Implementation of Electronic Architecture for Cloud Robotics and Human-Robot-Environment Interaction Strategy Applied to SmartWalker
    (Universidade Federal do Espírito Santo, 2021-12-13) Rocha Júnior, Joelson de Carvalho; Frizera Neto, Anselmo; https://orcid.org/0000000206873967; http://lattes.cnpq.br/8928890008799265; Alsina, Pablo Javier; Diaz, Camilo Arturo Rodriguez; Mello, Ricardo Carminati de
    Techniques for Human-Robot-Environment Interaction allow sharing control between assistive devices, such as smart walkers, and its users by taking into account the human motion intention and dynamic environments composed of objects and people. Smart Walkers are service robots equipped with a series of sensors and actuators to provide locomotion assistance to impaired people. The complexity in the algorithms to process all the sensors data push researchers to study and explore concepts of cloud computing, called cloud robotic paradigms, in such platforms. This dissertation presents the design and development of an electronic architecture for cloud robotics applied to Smart Walker. Through this implementation, the robotic device, from now called UFES CloudWalker, is capable of acquiring and transferring data to a robust virtual machine which process and convert them in to control signals to the robot actuators. This Master’s Thesis presents a study of smart walkers as assistive devices, as well as, control interaction strategies between the human, the robotic device and the environment. Moreover, we developed a robot environment interaction strategy which was evaluated in simulation and validated in real environment. The results showed the reliability of this strategy and boosted the development of a Human-Robot-Environment Interaction strategy in the same robotic device by adding information of the user’s legs. Finally, we validated this strategy in real environment with static and dynamic obstacles. The results show that the UFES CloudWalker adapts its behaviour accordingly changes in the environment and the user motion intentions.
  • Nenhuma Miniatura disponível
    Item
    Handling complex smart walker interaction strategies with Behavior Trees
    (Universidade Federal do Espírito Santo, 2022-10-24) Cardoso, Paula Alcantara; Frizera Neto, Anselmo; https://orcid.org/0000000206873967; http://lattes.cnpq.br/8928890008799265; Alsina, Pablo Javier; Lima, Eduardo Rocon de
    Walking is an activity that requires mastering stability and precision in order to be learned. Between the ages of 8 and 10, gait becomes an automatic activity, which once mastered does not depend on the attention of individuals. Mechanical factors and diseases, such as Parkinson’s and spinal cord injuries, as well as physical and cognitive conditions, can contribute to the quality of gait, which starts to present different types of disorders. With the increase of life expectancy and the share of the population over 65 years old, there is a concern regarding the demands for accessibility, rehabilitation and assistance, since they suffer from the reduction of their balance and mobility capacities. In this context, mobility assistance devices are valuable options to meet the needs of their users. Walkers, in particular, are alternatives for those who have residual motor skills. Its adoption postpones the use of wheelchairs and encourages the independence of its users. The inclusion of technologies, such as sensors and actuators, in the structure of walkers makes them intelligent, as they allow the incorporation of new functionalities that provide greater and better assistance for locomotion. The devices called robotic or smart walkers have several modules and control strategies that make their operation - and understanding - complex. This Master’s Dissertation proposes the inclusion of an artificial intelligence algorithm, based on a hierarchical architecture, for decision making that is capable of integrating several control strategies human-robot-environment interactions in the UFES CloudWalker. The algorithm implemented was the Behavior Tree, a structure that allows switching between controllers in a modular and reactive way. The system was validated by volunteers who performed a series of tasks aimed at evaluating the global performance of the smart walker. As a result, the system proved to be able to handle complex interactions between user, walker and the environment during navigation.