robots with limited sensing and/or actuating capabilities that cooperate (explicitly
or implicitly) based on local communications and sensing in order to complete a
mission. Its inherent redundancy provides flexibility and robustness to failures and
environmental disturbances which guarantee the proper completion of the required
task. At the same time, human intuition and cognition can prove very useful in
extreme situations where a fast and reliable solution is needed. This idea led to the
creation of the field of Human-Swarm Interfaces (HSI) which attempts to incorporate
the human element into the control of robotic swarms for increased robustness and
reliability. The aim of the present work is to extend the current state-of-the-art in HSI
by applying ideas and principles from the field of Brain-Computer Interfaces (BCI),
which has proven to be very useful for people with motor disabilities. At first, a
preliminary investigation about the connection of brain activity and the observation
of swarm collective behaviors is conducted. After showing that such a connection
may exist, a hybrid BCI system is presented for the control of a swarm of quadrotors.
The system is based on the combination of motor imagery and the input from a game
controller, while its feasibility is proven through an extensive experimental process.
Finally, speech imagery is proposed as an alternative mental task for BCI applications.
This is done through a series of rigorous experiments and appropriate data analysis.
This work suggests that the integration of BCI principles in HSI applications can be
successful and it can potentially lead to systems that are more intuitive for the users
than the current state-of-the-art. At the same time, it motivates further research in
the area and sets the stepping stones for the potential development of the field of
Brain-Swarm Interfaces (BSI).
This dissertation studies a phase based oscillator constructed with a second order dynamic system and a forcing function based on the phase angle of the system. This produces a bounded control signal that can alter the damping and stiffens properties of the dynamic system. It is shown analytically and experimentally that it is stable and robust. It can handle perturbations remarkably well. The forcing function uses the states of the system to produces stable oscillations. Also, this work shows the use of the phase based oscillator in wearable robots to assist periodic human motion focusing on assisting the hip motion. One of the main problems to assist periodic motion properly is to determine the frequency of the signal. The phase oscillator eliminates this problem because the signal always has the correct frequency. The input requires the position and velocity of the system. Additionally, the simplicity of the controller allows for simple implementation.
Background: Robotic devices have been utilized in gait rehabilitation but have only produced moderate results when compared to conventional physiotherapy. Because bipedal walking requires neural coupling and dynamic interactions between the legs, a fundamental understanding of the sensorimotor mechanisms of inter-leg coordination during walking, which are not well understood but are systematically explored in this study, is needed to inform robotic interventions in gait therapy.
Methods: In this study we investigate mechanisms of inter-leg coordination by utilizing novel sensory perturbations created by real-time control of floor stiffness on a split-belt treadmill. We systematically alter the unilateral magnitude of the walking surface stiffness and the timing of these perturbations within the stance phase of the gait cycle, along with the level of body-weight support, while recording the kinematic and muscular response of the unperturbed leg. This provides new insight into the role of walking surface stiffness in inter-leg coordination during human walking. Both paired and unpaired unadjusted t-tests at the 95 % confidence level are used in the appropriate scenario to determine statistical significance of the results.
Results: We present results of increased hip, knee, and ankle flexion, as well as increased tibialis anterior and soleus activation, in the unperturbed leg of healthy subjects that is repeatable and scalable with walking surface stiffness. The observed response was not impacted by the level of body-weight support provided, which suggests that walking surface stiffness is a unique stimulus in gait. In addition, we show that the activation of the tibialis anterior and soleus muscles is altered by the timing of the perturbations within the gait cycle.
Conclusions: This paper characterizes the contralateral leg’s response to ipsilateral manipulations of the walking surface and establishes the importance of walking surface stiffness in inter-leg coordination during human walking.
We propose parallel algorithms for stability analysis of two classes of systems: 1) Linear systems with a large number of uncertain parameters; 2) Nonlinear systems defined by polynomial vector fields. First, we develop a distributed parallel algorithm which applies Polya's and/or Handelman's theorems to some variants of parameter-dependent Lyapunov inequalities with parameters defined over the standard simplex. The result is a sequence of SDPs which possess a block-diagonal structure. We then develop a parallel SDP solver which exploits this structure in order to map the computation, memory and communication to a distributed parallel environment. Numerical tests on a supercomputer demonstrate the ability of the algorithm to efficiently utilize hundreds and potentially thousands of processors, and analyze systems with 100+ dimensional state-space. Furthermore, we extend our algorithms to analyze robust stability over more complicated geometries such as hypercubes and arbitrary convex polytopes. Our algorithms can be readily extended to address a wide variety of problems in control such as Hinfinity synthesis for systems with parametric uncertainty and computing control Lyapunov functions.