Aand1/Master_Thesis_Local_Planning_Algorithms_In_ROS

The main goal of this work is to compare several local planning algorithms (planners). The assumption is to compare, two algorithms which are already implemented in ROS environment and two selected motion planning algorithms. Based on the performed research of the available motion planning approaches, two algorithms have been selected, Potential field based algorithm and BUG0 algorithm (Chapters 2-3). In order to achieve the main goal of this master thesis, the whole test environment based on ROS has been created. The Gazebo2 simulator and the Pioneer 3-DX robot model have been used in that order. The Gazebo2 simulator and the robot model have been configured with the ROS environment compatibility (Chapter 4). Selected algorithms have been implemented in Python 2.7 programming language. Implemented algorithms and ROS algorithms have been configured with previously created test environment (Chapters 5-6). The robot working area became the rectangular building wit dimensions, 100x30[m]. About 40 obstacles, with different size, have been created in the building (Chapter 7.1). Next, the tests have been performed, in the prepared working area, in order to obtain the optimal parameters sets for each algorithm.

Python