Mapping and Navigation on Rough Surface with LIDAR and IMU

The robotics sector is one of the most affected areas by the developments and revisions in technology. Currently, the systems used in housework have been autonomized to minimize human impact. Autonomous systems targeting innovations perform location determination, mapping, and route planning functions using artificial intelligence algorithms. These systems are sensitive and costly devices. Surface defects in the environment can damage the electronic circuit elements of the robots and cause the algorithms to work incorrectly. To minimize the damage and cost in these systems, it is desired to make a platform modeling integrated with the mobile robot, which will add a new dimension to the 2D mapped environment. The ROS software package has been preferred to make sense of the LIDAR sensor's data for indoor mapping. A 2D map of the environment was created with SLAM algorithms. The slope data obtained from the IMU sensor was added to the 2D map in the simulation environment and a 3D map has been created. Thus, it was ensured that the robot reached the target by using route planning algorithms on the updated map. Thanks to route planning, the robot reaches the target in the fastest way with the minimum cost, considering the surface defects. Thus, an improvement of 33,32% was observed by comparing the route drawn at the beginning and the route with the lowest cost.