  Inspecting petrochemical pipelines is challenging due to hazardous materials,
narrow diameters, and inaccessible locations. Mobile robots are promising for
autonomous pipeline inspection and mapping. This project aimed to simulate and
implement a robot capable of simultaneous localization and mapping (SLAM) in an
indoor maze-like environment representing simplified pipelines. The approach
involved simulating a differential drive robot in Gazebo/ROS, equipping it with
sensors, implementing SLAM using mapping, and path planning with move_base. A
physical robot was then built and tested by manually driving it in a
constructed maze while collecting sensor data and mapping. Sensor fusion of
wheel encoders, Kinect camera, and inertial measurement unit (IMU) data was
explored to improve odometry and mapping accuracy without encoders. The final
map had reasonable correspondence to the true maze despite lacking wheel
encoders. In summary, results show the feasibility of using ROS-based SLAM for
pipeline inspection if accounting for real-world complexities.
