INTRODUCTION
Autonomous robots with
mobile capability are finding their place in numerous application fields. Some
typical examples of these application fields are factory automation, service
application, and hazardous environments such as dangerous zones in nuclear
power stations, space exploration, material handling in hospital and security
guarding. The key requirement for performing these tasks is navigation.
Navigation is the ability of a mobile robot to reach the target safely without
human assistance. Thus the main issues that need to be addressed in mobile
robot navigation are reactive obstacle avoidance and target acquisition. Vision
based sensing for autonomous navigation is a powerful and popular method due to
its ability to provide detailed information of environment which may not be
available using combinations of other types of sensors and has been addressed
by many researchers.
DESCRIPTION
Neural navigators
perceive their knowledge and skills from a demonstrating action and also suffer
from a very slow convergence process and lack of generalization due to limited
patterns to represent complicated environment. However, neural networks that
can be implemented with relatively modest computer hardware could be very
useful. Although the aforementioned techniques successfully solve the robot
navigational problem, there always remains a need of lowering the system cost
further without compromising much on its efficiency and reliability.
The navigation task is
subdivided into hurdle avoidance and goal seeking tasks. Hurdle avoidance is
achieved with the help of one back ultrasonic sensor, two front IR sensors
& sonar sensor. The range data from these sensors is fed to inside the
microcontroller. Goal seeking behavior involves the data from GPS, GPS receiver
which is processed by another microcontroller. In this project for the demo
purpose we are giving the goal as left, right, forward commands because in room environment there will be
small changes in the GPS location co ordinates that robot may not consider it
as different location . The main microcontroller fetches the desired data and
generates motion commands for robot. A GSM modem is interfaced to the main
controller for selecting start and goal stations for robot inside the
university campus. Neural network simulation will be done by using MATLAB.
8051 architecture based AT89C52 microcontroller from
ATMEL is used to implement this project. Microcontroller acts as the heart of
this project, which Controls the whole system. It contains 256 RAM, 2k Flash, 2
Timers, 2 external interrupts, 1 UART, 32 GPIO’s, ISP programming support etc.
KEIL IDE is used to program the microcontroller and the coding will be done
using Embedded C.
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DIAGRAM