Simultaneous localization and mapping for mobile robots has been an active research field for several years with focus on the problems of accuracy and dependability of the data from the robot's peripherals. The position estimates for mobile and industrial robots is usually achieved by using the information from the global positioning system in an outdoor environment and for indoor environment, technologies such as LiDAR sensors and Infrared (IR) camera based motion capture systems such as VICON(TM) are used. The main issue with these approach for indoor navigation is the monetary cost to associated with these technologies.

The purpose of this thesis is to provide a different approach for position and motion estimation of a robot for indoor localization and navigation. The presented position estimation technique is developed as a cost effective and viable replacement for the above mentioned indoor navigation systems and other GPS denied areas. The problem of tracking the robot is handled by using a triangulation technique which uses depth measurement sensors. The experimental setup is based on multiple sensors running on individual computers, connected via a wireless network. The sensors used in this setup are characterized with regards to their localization capability. The position and motion estimation technique is experimentally verified by using the sensor work-space environment setup under different working conditions.