Modelling, Simulation, and Implementing ROS for Autonomous Navigation of Tracked Robot

This is the authors' abstract. We don't add key points for this paper.

This paper presents autonomous navigation and its implementation based on Robotic Operating System (ROS) for a nonholonomic autonomous tracked robot, whereas it handles a full design, implementation, dynamic modeling, and kinematic modeling of the robot. This paper applies robot localization using Adaptive Monte Carlo Localization (AMCL) which uses a particle filter to track the pose of a robot against a known map. It also uses mapping based on the mapping package. It provides laser-based SLAM (Simultaneous Localization and Mapping) mapping. The LIDAR is used to create a 2-D occupancy grid map. Path planning is established using the Dijkstra algorithm to plan a path to a goal position, using a persistent map created by the robot during the mapping process. Also, the robot was equipped with a camera module for image processing and detection of different objects for security purposes. The proposed system shows its capability for adaptation to road segments of different curvatures and the transitions between them.