An RTK-SLAM Dataset for Absolute Accuracy Evaluation in GNSS-Degraded Environments

The project addresses a specific technical gap in SLAM evaluation: the standard use of SE(3) alignment in Absolute Trajectory Error (ATE) calculation, which inadvertently masks global drift in RTK-integrated systems. This is highly relevant for georeferenced surveying where global coordinates matter more than relative consistency. With 0 stars and 5 forks at 9 days old, the project is in its infancy and functions primarily as a research artifact. Its defensibility is currently low (score 3) as it relies on the community's willingness to adopt a new benchmarking standard over established ones like KITTI or UrbanLoco. The 'moat' for datasets is usually 'data gravity'—becoming the standard against which all new papers must compare. While the insight regarding ATE alignment is technically sound and provides a 'novel combination' of geodetic principles with SLAM metrics, it lacks the volume of data or institutional backing to be a category-definer yet. Frontier labs are unlikely to compete here as this is a niche domain involving physical hardware and specialized surveying requirements. Displacement risk is moderate, as established datasets could simply adopt the 'non-aligned' evaluation script proposed here.