Successful terrestrial robots rely on the accuracy and robustness of their navigation algorithms and, in turn, the sensor information that feeds those algorithms. VSLAM and LIDAR systems can be impacted negatively when the environment cannot be tracked well, for example poor lighting, fast movements, and obstructions. During these conditions, highly accurate dead reckoning is crucial for maintaining performance and a smooth user experience. Autonomous systems relying solely on dead reckoning are even more dependent on high sensor accuracy to run without a camera or LIDAR. But each dead reckoning sensor has its own challenges – wheels can slip and fool their encoder, optical flow sensors measure distances differently depending on the surface, and IMUs are influenced by temperature changes and drift.