Autonomous Robot Navigation in a Real Environment Using Reinforcement Learning

A. Sohail

Autonomous robots are getting increasingly popular these days because of the applications they have from cleaning floor of a house to transporting goods from one place to another. In such environments, obstacles can cause damage to the robot and can also cause interrupt the robot from performing an operation. A robot should be able to navigate in an unknown environment by avoiding collisions with the obstacles. In this thesis, an algorithm for robot navigation in cluttered environment will be developed. Camera and LIDAR will be used to acquire the distance with obstacles which will help the robot to avoid collision. The problem of an unknown environment can be solved through Reinforcement Learning algorithms. The performance of the algorithm will be evaluated on how much time it takes before the first collision, using the robot in GET Lab.