Simultaneous localization & mapping application on unmanned airel vehicle(uav)

In view of today's technological achievements, robotics applications become more important. Increase in a information knowledge and extensive information sharing platforms and life speed nearly beyond the human capability. Within this speed in near future, daily time will not be enough for a mankind. Therefore man needs unmanned vehicles and robots to catch the time. In this study, a review and an application of Unmanned Vehicle concept is realized. Simultaneous Localization and Mapping Algorithm (SLAM) is currently most important area especially on vehicles. There are various appoaches and implementatation techniques are available. In this work, SLAM Implementation with Unmanned Airel Vehicles (UAV) were studied. Rotary-Wing UAV Structure is reviewed in detail. Also Bayes theory Framework is reviewed to implement Unmanned Algorithm bases. Under Bayes theory, recursive bayes theory is reviewed. Kalman filter based and Particle filter based implementation techniques are discussed. Also Robot Operating System (ROS) reviewed in details. At the end a Particle filter based application is realized with Robot Operating System (ROS) using Gmapping Algorithm and results are discussed.