Optical Navigation in Unstructured Dynamic Railroad Environments
This work addresses the need for cost-effective local navigation systems to replace expensive train management infrastructure, though it appears incremental as it builds on existing optical navigation methods.
The paper tackles the problem of estimating train motion in unstructured, dynamic railroad environments using only observations of the planar track bed, despite occlusions, and validates the approach with real rail scenarios.
We present an approach for optical navigation in unstructured, dynamic railroad environments. We propose a way how to cope with the estimation of the train motion from sole observations of the planar track bed. The occasional significant occlusions during the operation of the train limit the available observation to this difficult to track, repetitive area. This approach is a step towards replacement of the expensive train management infrastructure with local intelligence on the train for SmartRail 4.0. We derive our approach for robust estimation of translation and rotation in this difficult environments and provide experimental validation of the approach on real rail scenarios.