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MICROCONTROLLER BASED NEURAL NETWORK CONTROLLED LOW COST AUTONOMOUS VEHICLE

Platform : ieee embedded projects

IEEE Projects Years : 2012

MICROCONTROLLER BASED NEURAL NETWORK CONTROLLED LOW COST AUTONOMOUS VEHICLE

 

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.

 

 

COMPONENTS USED

  1. Microcontroller - P89V51RD2 – NxP.
  2. Alpha Numeric LCD Display.
  3. GSM Module.
  4. GPS.
  5. Ultrasonic Sensor.
  6. Sonar Sensor
  7. IR Sensor
  8. DC Motor.
  9.  L293 driver
  10. 4052 Multiplexer

 

 

BLOCK DIAGRAM

 

 

 

 

 

 

SOFTWARES USED

  1. Embedded C
  2. Keil Compiler
  3. Flash Magicitor tmperature  robot
  4. MATLAB

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