Fady Alnajjar

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The signals that the central nervous system (CNS) produces and sends to the muscles to effect movement are not entirely understood. Muscle synergy theory suggests that the central nervous system produces a small number of signals that pass through a network that distributes combinations of these signals to the muscles. Though these synergies are rather(More)
This work concerns practical issues surrounding the application of learning and memory in a real mobile robot towards optimal navigation in dynamic environments. A novel control system that contains two-level units (low-level and high-level) is developed and trained in a physical mobile robot ldquoe-Puckrdquo. In the low-level unit, the robotpsilas task is(More)
Muscle redundancy allows the central nervous system (CNS) to choose a suitable combination of muscles from a number of options. This flexibility in muscle combinations allows for efficient behaviors to be generated in daily life. The computational mechanism of choosing muscle combinations, however, remains a long-standing challenge. One effective method of(More)
In this paper, we study the relation between neural dynamics and robot behavior to develop self-organization algorithm of spiking neural network applicable to autonomous robot. We first formulated a spiking neural network model whose inputs and outputs were analog. We then implemented it into a miniature mobile robot Khepera. In order to see whether or not(More)
The evolutionarily novel ability to keep ones body upright while standing or walking, the human balance, deteriorates in old age or can be compromised after accidents or brain surgeries. With the aged society, age related balance problems are on the rise. Persons with balance problems are more likely to fall during their everyday life routines. Especially(More)
The development of a method to feed proper environmental inputs back to the central nervous system (CNS) remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the(More)
Edge detection plays a significant role in assessing the capability level of the robot's vision. Accurate edge detection leads to better vision. The work in this paper was conducted by the inspiration of the biological concept of mammalian vision. That is, the retina enriches the edges in the view before passing it to the visual cortex in the brain for(More)