Mohammed Alhawary

Mohammed Alhawary

Active student


Master's Thesis Project: Reinforcement-learning-based navigation for autonomous mobile robots in unknown environments

Mobile robot navigation in an unknown environment is an important issue in autonomous robotics. Current approaches to solve the navigation problem (roadmap, cell decomposition and potential field) assume complete knowledge about the navigation environment. Thus, navigation in an unknown or a partially unknown environment can be phrased as a reinforcement learning (RL) problem. Since it is only possible to discover the optimal navigation plan through trail-and-error interaction with the environment.

The goal of this project is to control a simple mobile robot to navigate in an unknown environment with obstacles and slippery floor using reinforcement learning. The main tasks will be to navigate to a goal location in the shortest time avoiding the obstacles and to learn the slippage model to determine the best way to move on the floor.