Neuro-mechanical entrainment in a bipedal robotic walking platform

In this study, we investigated the use of van der Pol oscillators in a 4-dof embodied bipedal robotic platform for the purposes of planar walking. The oscillator controlled the hip and knee joints of the robot and was capable of generating waveforms with the correct frequency and phase so as to entrain with the mechanical system. Lowering its oscillation frequency resulted in an increase to the walking pace, indicating exploitation of the global natural dynamics. This is verified by its operation in absence of entrainment, where faster limb motion results in a slower overall walking pace

Robot Swinging Using van der Pol Nonlinear Oscillators

In this study, we investigated the use of van der Pol oscillators in a 2-dof embodied robotic platform for a swinging task. The oscillator controlled the hip and knee joints of the robot and was capable of generating waveforms with the correct frequency and phase so as to entrain with the mechanical system

Experimental comparison of the van der Pol and Rayleigh nonlinear oscillators for a robotic swinging task

In this paper, the effects of different lower-level building blocks of a robotic swinging system are explored, from the perspective of motor skill acquisition. The van der Pol and Rayleigh oscillators are used to entrain to the system’s natural dynamics, with two different network topologies being used: a symmetric and a hierarchical one. Rayleigh outperformed van der Pol regarding maximum oscillation amplitudes for every morphological configuration examined. However, van der Pol started large amplitude relaxation oscillations faster, attaining better performance during the first half of the transient period. Hence, even though there are great similarities between the oscillators, differences in their resultant behaviours are more pronounced than originally expected

Biped locomotion control through a biomimetic CPG-based controller

Modern concepts of motor learning favour intensivetrainingdirectedtotheneuralnetworksstimulation and reorganization within the spinal cord, the central pattern generator, by taking advantage of the neural plasticity. In the present work, a biomimetic controller using a system of adaptive oscillators is proposed to understand the neuronal principles underlying the human locomotion. A framework for neural control is presented, enabling the following contributions: a) robustness to external perturbations; b) flexibility to variations in the environmental constraints; and c) incorporation of volitional mechanisms for self-adjustment of gait dynamics. Phase modulation of adaptive oscillators and postural balance control are proposed as main strategies for stable locomotion. Simulations of the locomotion model with a biped robot in closed-loop control are presented to validate the implemented neuronal principles. Specifically, the proposed system for online modulation of previous learnt gait patterns was verified in terrains with different slopes. The proposed phase modulation method and postural balanced control enabled robustness enhancement considering a broader range of slope angles than recent studies. Furthermore, the system was also verified for tilted ground including different slopes in the same experiment and uneven terrain with obstacles. Adaptive Frequency Oscillators, under Dynamic Hebbian Learning Adaptation mechanism, are proposed to build a hierarchical control architecture with spinal and supra spinal centers with multiple rhythm-generating neural networks that drive the legs of a biped model. The proposed neural oscillators are based on frequency adaptation and can be entrained by sensory feedback to learn specific patterns. The proposed biomimetic controller intrinsically generates patterns of rhythmic activity that can be induced to sustain CPG function by specific training. This method provides versatile control, paving the way for the design of experimental motor control studies, optimal rehabilitation procedures and robot-assisted therapeutic outcomes.Exchange of views with the supervisors, Vítor Matos from ABSGroup and several colleagues from the Bioengineering Group of CSI Convarious issues have proven to be vitally important in promoting gradual development of this study as well as in highlighting and clarifying priority steps for the improvement of the research, by which my particular thanks are expressed to them. This work is supported by FCT with the reference project UID/EEA/04436/2013, by FEDER funds through the COMPETE 2020 Programa Operacional Competitividade e Internacionalizao (POCI) with the reference project POCI-01-0145-FEDER-006941. This research has been funded by the Commission of the European Union under the BioMot project - Smart Wearable Robots with Bioinspired SensoryMotor Skills (Grant Agreement number IFP7-ICT- 2013-10-611695).info:eu-repo/semantics/publishedVersio