Mechanisms of motor learning: by humans, for robots

Whenever we perform a movement and interact with objects in our environment, our central nervous system (CNS) adapts and controls the redundant system of muscles actuating our limbs to produce suitable forces and impedance for the interaction. As modern robots are increasingly used to interact with objects, humans and other robots, they too require to continuously adapt the interaction forces and impedance to the situation. This thesis investigated the motor mechanisms in humans through a series of technical developments and experiments, and utilized the result to implement biomimetic motor behaviours on a robot. Original tools were first developed, which enabled two novel motor imaging experiments using functional magnetic resonance imaging (fMRI). The first experiment investigated the neural correlates of force and impedance control to understand the control structure employed by the human brain. The second experiment developed a regressor free technique to detect dynamic changes in brain activations during learning, and applied this technique to investigate changes in neural activity during adaptation to force fields and visuomotor rotations. In parallel, a psychophysical experiment investigated motor optimization in humans in a task characterized by multiple error-effort optima. Finally a computational model derived from some of these results was implemented to exhibit human like control and adaptation of force, impedance and movement trajectory in a robot

Optimum Size of Nanorods for Heating Application

Magnetic nanoparticles (MNP's) have become increasingly important in heating applications such as hyperthermia treatment of cancer due to their ability to release heat when a remote external alternating magnetic field is applied. It has been shown that the heating capability of such particles varies significantly with the size of particles used. In this paper, we theoretically evaluate the heating capability of rod-shaped MNP's and identify conditions under which these particles display highest efficiency. For optimally sized monodisperse particles, the power generated by rod-shaped particles is found to be equal to that generated by spherical particles. However, for particles which have a dispersion in size, rod-shaped particles are found to be more effective in heating as a result of the greater spread in the power density distribution curve. Additionally, for rod-shaped particles, a dispersion in the radius of the particle contributes more to the reduction in loss power when compared to a dispersion in the length. We further identify the optimum size, i.e the radius and length of nanorods, given a bi-variate log-normal distribution of particle size in two dimensions

Ultrasonic Enhanced Liquefaction and Saccharification of Corn for Bio-Fuel Production

Dry grind corn milling does not reach full efficiency of starch conversion to sugars and subsequently to ethanol because of limitations in the milling process. This paper examines the use of high-power ultrasonics to enhance the release of fermentable sugars from milled dry corn. In this work, 20 kHz ultrasonic energy was used to pretreat corn mash prior to enzymatic conversion of corn starch to glucose in a batch-mode. The ultrasonic amplitude was varied from 0, 191 to 320 µm pp . The corn mash was sonicated for 0 (control), 20 and 40 seconds. Other experimental variables that were studied included the effect of temperature and pretreatment sequencing, e.g., ultrasonic pretreatment before and after enzyme addition. It was found that the reaction rate kinetics of the enzymatic reactions increased threefold for sonicated samples. Energy balance (efficiency) analysis indicated that ultrasound pretreatment released twice as much energy (as sugar) when introduced during pretreatment. Based on scanning electron microscopy examination and particle size analysis, the enhancement of the conversion was primarily attributed to particle size reduction, resulting in an increase in the surface area to volume ratio, which in turn increased the available enzymatic reaction sites. One of the most striking findings was that enzymes were not degraded by low level ultrasonication. In addition, the most significant increase in sugar yield was seen when the enzymes were added before ultrasonic pretreatment. Ultrasound has the potential to enhance the ethanol yield from cornstarch and reduce the production cost significantly in commercial dry corn milling ethanol plants