Absolute Localization in Feature-poor Industrial Confined Spaces

Autonomous inspection of dark, confined, and ambiguous spaces requires robotic platforms to utilize accurate and reliable localization systems to operate safely and reliable. This paper presents an absolute localization system for highly ambiguous spaces, using visual inertial odometry and GPU based point cloud registrations for limited field of view sensors. Extracted structural elements from the sensor scans, along side IMU measurements, are used to limit the search area for the GPU based point cloud registrations. The 3D registrations are then fused with a visual-inertial odometry estimate in an Extended Kalman Filter, to provide a fast and accurate absolute pose estimate. The proposed localization system is tested in both a simulated environment and in a mock-up model of a chemical