Ellaithy: Design and implementation of path planning and control of a mobile robot

27.08.2019, 10.00 Uhr, APB 1096

Einladung zur Präsentation der Bachelorarbeit von Mohamad Ellaithy

Thema: “Design and implementation of path planning and control of a mobile robot”

Betreuer: Gökhan Akgün

Abstract: Autonomous navigation is a subject undergoing intense studies nowadays. The main aspects for a mobile robot to be considered autonomous is to be able to track its position at each time instance and to avoid any faced obstacles to reach a specified target. The mobile robot used in this work was a four wheeled vehicle. In this thesis both odometry and obstacle avoidance algorithms were implemented. Despite the fact that odometry was usually calculated using encoders mounted on the wheels to get ticks count, the used simulator did not have a model for the encoder. Therefore, the ticks counts usually used in odometry calculations would not be available. As a result, odometry algorithm in this thesis was based on inertial measurement unit (IMU) sensors mounted on the wheels of the vehicle. Regarding obstacle avoidance, the algorithm implemented in this thesis is a combination of several blocks. These blocks will aid the vehicle to avoid obstacles and navigate a user desired distance in a defined direction. The odometry and obstacle avoidance algorithm were implemented in C++ in a Robot operating system (ROS) environment. In addition, the odometry algorithm was implemented in HLS and integrated in a block design to be ready to run on a field-programmable gate array (FPGA). Specifically, the FPGA and the personal computer (PC) were connected using Ethernet and the block design that contains the odometry algorithm was accelerated on the FPGA using Petalinux. The results of odometry calculations while avoiding obstacles for the simulator, software and hardware versions of the algorithm were tested on the simulator. Then, the results were compared where the effectiveness of the proposed algorithms were verified on the simulator. Results of the algorithms showed successful odometry computations with an excellent accuracy for indoor environments compared to the outputs of the simulator.