ROBOTIC ARM USING ARTIFICIAL INTELLIGENCE

Abstract

This report focuses on the
replication of human hand movements using
computer vision to control a robotic arm. The
chosen robotic arm, designed by Gavel LAN
GEVIN, a French sculptor and designer, is
enhanced with computer vision and deep
learning capabilities, extending its applications to
agriculture, transportation, healthcare,
manufacturing, and more.
The project's primary objective is to improve
interactivity and user-friendliness in open-source
robotic arm control. Deep learning proves
instrumental in solving complex problems such
as image recognition, allowing the development
of advanced robotic systems capable of
performing tasks previously deemed challenging
or impossible.
To achieve the goal of creating a robotic arm
responsive to human hand movements, the
project involves the detection and classification
of hand gestures using computer vision. To create
a robotic arm that can detect the movements of
the human hand, the data is then transmitted to
the computer and then to the microcontroller
which process the information and sends
commands to the robotic arm to perform a
specific action. The gathered data is transmitted
to a computer, which processes the information
and sends commands to the microcontroller
connected to the robotic arm. This approach
allows for a more natural and intuitive control
method, as operators can use hand gestures that
mimic their own movements closely. This not
only enhances accuracy but also reduces operator
fatigue and the risk of injuries.