Investigation Of Ros Based Vehicle State Estimation With Uncertainties - Siti Nuraini, Che Huhaimi (2022)
This thesis proposed to examine ROS (Robot operating system) based vehicle state estimation considering uncertainties. ROS is a middleware between software and hardware. It also deals with the Kalman filter (KF) via different case studies where This approach is aimed to provide better estimation for mobile robots. Based on different case study ROS play an important role to evaluate mobile robot performance referring to its environment. ROS provides some convenient packages with ROS nodes and the SLAM algorithms that make the formation problem easier to solve. The light detection and ranging (LiDAR) sensor as obstacle detection are used to give information for this analysis in order to gain information from the surrounding where it helps to avoid obstacles. The 360-degree LiDAR sensor also was equipped in the turtlebot3 burger that was used in the laboratory setup. The simulation also involved a gazebo 3D simulator and mapping in Rviz visualization for map generation. Besides, the SLAM algorithm is used to give a picture of the robot to simultaneously map while locating itself. The preliminary result of this experiment illustrates that the Turtlebot3 Burger can avoid the obstacle on its way effectively from any starting point until that Turtlebot3 burger can reach its destination safely and it is expected the turtlebot3 burger can avoid any type of obstacle.