Doutorado em Engenharia Elétrica

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Navegando Doutorado em Engenharia Elétrica por Assunto "Admittance control"

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    Admittance control of a robotic knee orthosis based on motion intention through sEMG of trunk muscles
    (Universidade Federal do Espírito Santo, 2017-12-04) Parra, Ana Cecilia Villa; Frizera Neto, Anselmo; Bastos Filho, Teodiano Freire; Ferreira, Andre; Caldeira, Eliete Maria de Oliveira; Rocon, Eduardo; Bó, Antonio Padilha Lanari
    The population that requires devices for motion improvement has increased considerably, due to aging and neurological impairments. Robotic devices, such as robotic orthosis, have greatly advanced with the objective of improving both the mobility and quality of life of people. Clinical researches remark that these devices, working in constant interaction with the neuromuscular and skeletal human system, improves functional compensation and rehabilitation. Hence, the users become an active part of the training/rehabilitation, facilitating their involvement and improving their neural plasticity. For this purpose, control approaches based on motion intention have been presented as a novel control framework for robotic devices. This work presents the development of a novel robotic knee exoskeleton controlled by motion intention based on sEMG, which uses admittance modulation to assist people with reduced mobility and improve their locomotion. For recognition of the lower-limb motion intention, sEMG signals from trunk are used, which implies a new approach to control robotic assistive devices. The control system developed here includes a stage for human-motion intention recognition (HMIR) system, which is based on techniques to classify motion classes related to knee joint. The motion classes that are taken into account are: stand-up, sit-down, knee flexionextension, walking, rest in stand-up position and rest sit-down position. For translation of the users intention to a desired state for the robotic knee exoskeleton, the system includes a finite state machine, in addition to admittance, velocity and trajectory controllers, which has also the function of stopping the movement according to the users intention. This work also proposes a method for on-line knee impedance modulation, which generates variable gains through the gait cycle for stance control during gait. The proposed HMIR system showed, in off-line analysis, an accuracy between 76% to 83% to recognize motion intention of lower-limb muscles, and 71% to 77% for trunk. Experimental on-line results of the controller showed that the admittance controller proposed here offers knee support in 50% of the gait cycle, and assists correctly the motion classes. A positive effect of the controller on users regarding safety during gait was also found, with a score of 4 in a scale of 5. Thus the robotic knee exoskeleton introduced here is an alternative method to empower knee movements using motion intention based on sEMG signals from lower limb and trunk muscles.
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    Human-robot-environment interaction strategies for walker-assisted gait
    (Universidade Federal do Espírito Santo, 2018-12-19) Jiménez Hernández, Mario Fernando; Bastos Filho, Teodiano Freire; Frizera Neto, Anselmo; Lima, Eduardo Rocon de; Mauledoux Monroy, Mauricio Felipe; Ferreira, Andre; Caldeira, Eliete Maria de Oliveira
    Smart Walkers (SWs) are robotic devices that may be used to improve balance and locomotion stability of people with lower-limb weakness or poor balance. Such devices may also offer support for cognitive disabilities and for people that cannot safely use conventional walkers, as well as allow interaction with other individuals and with the environment. In this context, there is a significant need to involve the environment information into the SW's control strategies. In this Ph.D. thesis, the concept of Human-Robot-Environment Interaction (HREI) for human locomotion assistance with a smart walker developed at UFES/Brazil (turned UFES's Smart Walker - USW) is explored. Two control strategies and one social navigation strategy are presented. The first control strategy is an admittance controller that generates haptic signals to induce the tracking of a predetermined path. When deviating from such path, the proposed method varies the damping parameter of the admittance controller by means of a spatial modulation technique, resulting in a haptic feedback, when is perceived by the user as a hard locomotion towards the undesired direction. The second strategy also uses an admittance controller to generate haptic signals, which guide the user along a predetermined path. However, in this case, the angular velocity of the smart walker is implemented as a function of a virtual torque, which is defined using two virtual forces that depend on the angular orientation error between the walker and the desired path. Regarding the navigation strategy, it involves social conventions defined by proxemics, and haptic signals generated through the spatial modulation of the admittance controller for a safe navigation within confined spaces. The USW uses a multimodal cognitive interaction composed of a haptic feedback and a visual interface with two LEDs to indicate the correct/desired direction when necessary. The proposed control strategies are suitable for a natural HREI as demonstrated in the experimental validation. Moreover, this Ph.D. thesis presents a strategy to obtain navigation commands for the USW based on multi-axial force sensors, in addition to a study of the admittance control parameters and its influence on the maneuverability of the USW, in order to improve its HREI.