الفهرس 
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Abstract
Mobile robots has an important status in real life and industrial
applications. In this thesis human–robot interaction as a part of strive
researchers is represented. This interaction is not only by communication,
but it is an interaction by human‟s emotional state. The current research
represents new techniques and an implementation of voice autonomous
robot system. It is divided into five stages. The first stage is a pretreatment
stage known as Digital Signal Processing (DSP), for recording the orders of
speaker‟s voice to build a database and to manipulate orders. The noise
cancelation of recorded signal that is applied by filtering techniques is the
second stage. The third stage is the Speech Recognition (SR) algorithms
which use the enhancement of the Isolated Word Command Technique
(IWCT) to achieve more accuracy of the voice signal. Fuzzy Logic Control
(FLC) that examines the parameters of voice signal with a Voice Emotional
Recognition (VER) had measured with three emotional modes: calm,
normal and anger. Controlling the velocity and azimuth angle of the
Tricycle Mobile Robot (TMR), considered as the fourth stage, was
discussed and examined by three methods. In the final stage, results were
collected from previous stages combined for the brain of the Tricycle
Mobile Robot (TMR) to drive each motor with specified order. An effort
was made to investigate and control the velocity and azimuth of TMR by
using the fuzzy logic controller alone, using a fuzzy logic controller along
with a PID controller and using the Fuzzy Inference System (FIS) with a
lookup table. Each controller is examined with trapezoidal, triangular and
Gaussian membership function, and all the obtained results are compared.
The results proved that the FLC has the best output response and the
control signal at the sinusoidal input. Also, the result showed that minimum
error signal occured for FLC with triangular membership function at the
unit sinusoidal input.