Luqman Hakim

/*****************************************************************************
  * @title  EXTI,PWM,UART data parsing,motor control
  * @author Luqman Hakim
  * @date  latest build:1 june 2015
  * @brief  example how to read rotary encoder by external interrupt and TIMER4, how to
  * generate pwm by TIMER3 to control motor movement, and how to parse received
  * data from UART3 and pass the data to pwm duty cycle.
  * note follow the link in txt file i provided and download the rar            file containing the project files
              see #defines macro in included defines.h file
  * see function declaration in included main_function.h file
  *            this is just example code, the implementation of the code        may differ for your hardware configuration *******************************************************************************/

*****************************************************************************
  * @title  USART1,TIMER2,ADC1,GPIOs(input & output)
  * @author  Luqman Hakim, student of EEPIS(Electronics Engineering Polytechnic Institute of Surabaya)
  * @date    first build :12 Mar 2015
  *          latest build:25 Mar 2015
  * @brief  basic GPIO, UART,TIMER, and ADC example
  *          This project is made using Coocox CoIDE which is an open source ARM microcontroller developing IDE based on Eclipse.
  *          This project uses arm-none-eabi-gcc -mcpu as the toolchain. you have to use this toolchain if you develop under Coocox CoIDE.
follow the link in txt file i provided and download the rar            file containing the project files
*******************************************************************************/

Navigation system and path path planning are needed for robot so the
robot can do maneuver in its environment. Some methods can be applied
as the navigation system of the robot in indoor environment, one of the
method is vision based location positioning that implement image
database and location model, The image sequence is obtained by a
wearable mobile PC with camera, then the obtained image is compared
with the image database. The disadvantage of this method are the lighting
around the environment that can make the visual recognition fails. And
also the processing unit demands high power input, so this method is not
efficient if applied to mobile robot that has very few functionality. The
other method is odometri, a method to determine the relative position of
the robot by calculating the wheel rotation. Of course this method will not
work well in environment that has slippery ground making the rotary
encoder sensor does miss reading. This research presents the
implementation of indoor positioning system as the navigation system of
the mobile robot. This system uses wireless sensor network to do ranging
measurement then do a calculation using trilateration method to
determine the positioning of the mobile robot. Also magnetometer sensor
used to determine the heading of the robot. From the examination we
acquire that path planning using this indoor positioning system has
average error of 4,34% when robot moves from initial position (0,0)m to
target position (2,2)m and average error of 3,34 when robot moves from
initial position (0,0)m to target position (4,4)m.
Keyword : mobile robot, wireless sensor network, navigation, indoor
positioning