CIOT: Constraint-Enhanced Inertial-Odometric Tracking for Articulated Dump Trucks in GNSS-Denied Mining Environments

The ongoing electrification in all domains relies on strong increase in raw material extraction. Autonomous dump trucks are key to facilitating this. The automation requires the development of new localization approaches, as deep open-pit mines are challenging for satellite-based localization systems. Deep funnel-shaped mines reduce the sky-view angle from a certain position onward so that few to no satellites are visible. Therefore, we introduce a new wheel-odometry-aided navi- gation filter for articulated vehicles that fuses measurements from an inertial measurement unit (IMU), global navigation satellite systems (GNSS), and wheel encoders. Non-holonomic constraints are incorporated by assuming the lateral velocity of each wheel to be zero. We present two different measurement models that either use the wheel encoder signals of the rear wheels or all wheels of the articulated vehicle. This approach enables articulated vehicles to cope with the challenges of open-pit mines. The developed navigation filter is evaluated experimentally with an articulated dumper in two scenarios: A paved parking lot and a gravel pit. With the proposed method, we achieved a mean position error of 0.21 m during a 190 s test drive in the gravel pit with a simulated GNSS interruption of 90 s. This is an improvement of 64 m compared to a state- of-the-art navigation filter that fuses only inertial and GNSS measurements.